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        "import warnings\n",
        "warnings.filterwarnings('ignore')\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "from sklearn.model_selection import train_test_split, GridSearchCV, cross_val_score\n",
        "from sklearn.feature_selection import SelectKBest, f_classif\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.ensemble import RandomForestClassifier\n",
        "from sklearn.svm import SVC\n",
        "from sklearn.metrics import accuracy_score, classification_report, confusion_matrix\n",
        "from sklearn.preprocessing import StandardScaler"
      ]
    },
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              "      <td>Ojukwu Balewa Awolowo (O.B.A.) Public Library ...</td>\n",
              "      <td>Establishing a free, world-class, public libra...</td>\n",
              "      <td>100000.0</td>\n",
              "      <td>120.0</td>\n",
              "      <td>failed</td>\n",
              "      <td>ojukwu-balewa-awolowo-oba-public-library-of-ni...</td>\n",
              "      <td>False</td>\n",
              "      <td>...</td>\n",
              "      <td>60 days 00:00:00.000000000</td>\n",
              "      <td>60 days 00:00:01.000000000</td>\n",
              "      <td>1</td>\n",
              "      <td>60</td>\n",
              "      <td>60</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>859724515</td>\n",
              "      <td>{\"small\":\"https://ksr-ugc.imgix.net/assets/011...</td>\n",
              "      <td>MASTIZE - [mas-TAHYZ, MAS-tahyz]  - to spread</td>\n",
              "      <td>Goal: Introducing a new word into the English ...</td>\n",
              "      <td>5000.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>failed</td>\n",
              "      <td>mastize-mas-tahyz-mas-tahyz-to-spread</td>\n",
              "      <td>False</td>\n",
              "      <td>...</td>\n",
              "      <td>30 days 00:00:00.000000000</td>\n",
              "      <td>30 days 00:00:00.000000000</td>\n",
              "      <td>0</td>\n",
              "      <td>30</td>\n",
              "      <td>30</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>1613604977</td>\n",
              "      <td>{\"small\":\"https://ksr-ugc.imgix.net/assets/012...</td>\n",
              "      <td>Synopse der EU-DSGVO - Artikel, Erwägungsgründ...</td>\n",
              "      <td>Zu den Artikeln der DSGVO sind die korrespondi...</td>\n",
              "      <td>3222.0</td>\n",
              "      <td>356.0</td>\n",
              "      <td>failed</td>\n",
              "      <td>synopse-der-eu-dsgvo-artikel-erwagungsgrunde-bdsg</td>\n",
              "      <td>False</td>\n",
              "      <td>...</td>\n",
              "      <td>32 days 06:02:33.000000000</td>\n",
              "      <td>32 days 06:02:33.000000000</td>\n",
              "      <td>0</td>\n",
              "      <td>32</td>\n",
              "      <td>32</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 68 columns</p>\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
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              "            + ' to learn more about interactive tables.';\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
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        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "full_1 = full.drop(['Unnamed: 0', 'id', 'photo', 'friends', 'is_starred', 'is_backing', 'permissions'], axis=1)"
      ],
      "metadata": {
        "id": "Sbvtt_6XFiT-"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "full_1.head(1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        },
        "id": "mEDqjMD2FmLl",
        "outputId": "1d0223a3-75e1-492d-f306-6d59418c1883"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
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              "                                                name  \\\n",
              "0  Auntie Di's Music Time Sign ASL for Hearing an...   \n",
              "\n",
              "                                               blurb    goal  pledged   state  \\\n",
              "0  MTS ASL Curriculum Workbook is a reproducible ...  1500.0      0.0  failed   \n",
              "\n",
              "                                                slug  disable_communication  \\\n",
              "0  auntie-dis-music-time-sign-asl-for-hearing-and...                  False   \n",
              "\n",
              "  country currency currency_symbol  ...          launch_to_deadline  \\\n",
              "0      US      USD               $  ...  36 days 20:47:24.000000000   \n",
              "\n",
              "       launch_to_state_change create_to_launch_days launch_to_deadline_days  \\\n",
              "0  36 days 20:47:24.000000000                    17                      36   \n",
              "\n",
              "  launch_to_state_change_days  SuccessfulBool  USorGB  TOPCOUNTRY  \\\n",
              "0                          36               0       1           1   \n",
              "\n",
              "   LaunchedTuesday DeadlineWeekend  \n",
              "0                0               0  \n",
              "\n",
              "[1 rows x 61 columns]"
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              "<p>1 rows × 61 columns</p>\n",
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              "          const element = document.querySelector('#df-4a90ccde-1061-4b31-885d-b428ab1dd4d2');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "            + ' to learn more about interactive tables.';\n",
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    {
      "cell_type": "code",
      "source": [
        "full_1.info()"
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        "id": "4rGHq1rfFkNh",
        "outputId": "fa0a0e40-7dde-4b06-b896-a025ba11a357"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 20632 entries, 0 to 20631\n",
            "Data columns (total 61 columns):\n",
            " #   Column                       Non-Null Count  Dtype  \n",
            "---  ------                       --------------  -----  \n",
            " 0   name                         20632 non-null  object \n",
            " 1   blurb                        20627 non-null  object \n",
            " 2   goal                         20632 non-null  float64\n",
            " 3   pledged                      20632 non-null  float64\n",
            " 4   state                        20632 non-null  object \n",
            " 5   slug                         20632 non-null  object \n",
            " 6   disable_communication        20632 non-null  bool   \n",
            " 7   country                      20632 non-null  object \n",
            " 8   currency                     20632 non-null  object \n",
            " 9   currency_symbol              20632 non-null  object \n",
            " 10  currency_trailing_code       20632 non-null  bool   \n",
            " 11  deadline                     20632 non-null  object \n",
            " 12  state_changed_at             20632 non-null  object \n",
            " 13  created_at                   20632 non-null  object \n",
            " 14  launched_at                  20632 non-null  object \n",
            " 15  staff_pick                   20632 non-null  bool   \n",
            " 16  backers_count                20632 non-null  int64  \n",
            " 17  static_usd_rate              20632 non-null  float64\n",
            " 18  usd_pledged                  20632 non-null  float64\n",
            " 19  creator                      20632 non-null  object \n",
            " 20  location                     20587 non-null  object \n",
            " 21  category                     18743 non-null  object \n",
            " 22  profile                      20632 non-null  object \n",
            " 23  spotlight                    20632 non-null  bool   \n",
            " 24  urls                         20632 non-null  object \n",
            " 25  source_url                   20632 non-null  object \n",
            " 26  name_len                     20627 non-null  float64\n",
            " 27  name_len_clean               20627 non-null  float64\n",
            " 28  blurb_len                    20627 non-null  float64\n",
            " 29  blurb_len_clean              20627 non-null  float64\n",
            " 30  deadline_weekday             20632 non-null  object \n",
            " 31  state_changed_at_weekday     20632 non-null  object \n",
            " 32  created_at_weekday           20632 non-null  object \n",
            " 33  launched_at_weekday          20632 non-null  object \n",
            " 34  deadline_month               20632 non-null  int64  \n",
            " 35  deadline_day                 20632 non-null  int64  \n",
            " 36  deadline_yr                  20632 non-null  int64  \n",
            " 37  deadline_hr                  20632 non-null  int64  \n",
            " 38  state_changed_at_month       20632 non-null  int64  \n",
            " 39  state_changed_at_day         20632 non-null  int64  \n",
            " 40  state_changed_at_yr          20632 non-null  int64  \n",
            " 41  state_changed_at_hr          20632 non-null  int64  \n",
            " 42  created_at_month             20632 non-null  int64  \n",
            " 43  created_at_day               20632 non-null  int64  \n",
            " 44  created_at_yr                20632 non-null  int64  \n",
            " 45  created_at_hr                20632 non-null  int64  \n",
            " 46  launched_at_month            20632 non-null  int64  \n",
            " 47  launched_at_day              20632 non-null  int64  \n",
            " 48  launched_at_yr               20632 non-null  int64  \n",
            " 49  launched_at_hr               20632 non-null  int64  \n",
            " 50  create_to_launch             20632 non-null  object \n",
            " 51  launch_to_deadline           20632 non-null  object \n",
            " 52  launch_to_state_change       20632 non-null  object \n",
            " 53  create_to_launch_days        20632 non-null  int64  \n",
            " 54  launch_to_deadline_days      20632 non-null  int64  \n",
            " 55  launch_to_state_change_days  20632 non-null  int64  \n",
            " 56  SuccessfulBool               20632 non-null  int64  \n",
            " 57  USorGB                       20632 non-null  int64  \n",
            " 58  TOPCOUNTRY                   20632 non-null  int64  \n",
            " 59  LaunchedTuesday              20632 non-null  int64  \n",
            " 60  DeadlineWeekend              20632 non-null  int64  \n",
            "dtypes: bool(4), float64(8), int64(25), object(24)\n",
            "memory usage: 9.1+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###Goal Feature EDA"
      ],
      "metadata": {
        "id": "SRZXLTXP2KzP"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "full_1['goal'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xqxLzJv6L2CZ",
        "outputId": "1330f261-f3b8-4d8a-ca97-4af1d25c6206"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "10000.0     1480\n",
              "5000.0      1323\n",
              "50000.0     1302\n",
              "20000.0      946\n",
              "25000.0      839\n",
              "            ... \n",
              "370000.0       1\n",
              "25730.0        1\n",
              "55650.0        1\n",
              "622942.0       1\n",
              "55151.0        1\n",
              "Name: goal, Length: 1204, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "temp_df = full_1['goal']\n",
        "\n",
        "from scipy import stats\n",
        "z = np.abs(stats.zscore(temp_df))\n",
        "\n",
        "# Define a threshold (e.g. 3) for identifying outliers\n",
        "threshold = 0.068\n",
        "\n",
        "# Find the indices of the outliers\n",
        "outlier_indices = np.where(z > threshold)\n",
        "\n",
        "# Remove the outliers from the DataFrame\n",
        "df_clean = temp_df.drop(outlier_indices[0], axis=0)\n",
        "df_clean.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2EvAPDNHsDoz",
        "outputId": "b9c03e9a-dd0a-420e-a286-a69f9a9fcd4c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(14771,)"
            ]
          },
          "metadata": {},
          "execution_count": 78
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pd.DataFrame(df_clean).hist()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 474
        },
        "id": "fXE2FRP6s-fa",
        "outputId": "25b109ff-ce45-424b-a36a-c62819b43dad"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[<Axes: title={'center': 'goal'}>]], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 79
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pd.DataFrame(df_clean).boxplot(column=['goal'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 451
        },
        "id": "535LyJL6p-Pv",
        "outputId": "05a27b09-ccd1-4cbd-e1af-489b92775c77"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 80
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# full_1.drop(['goal_scaler'],axis=1,inplace=True)\n",
        "# from sklearn.preprocessing import StandardScaler\n",
        "# scaler = StandardScaler()\n",
        "# after_outlier_scaling_goal = scaler.fit_transform(pd.DataFrame(df_clean).values.reshape(-1,1))\n",
        "after_outlier_scaling_goal = np.log(df_clean)\n",
        "pd.DataFrame(after_outlier_scaling_goal).hist()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 474
        },
        "id": "oJMKsVdipgkx",
        "outputId": "92bb1a9c-b0dc-43a6-fec2-ba14f4bca0b7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[<Axes: title={'center': 'goal'}>]], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 88
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.set(style='whitegrid')\n",
        "plt.figure(figsize=(10, 6))\n",
        "feature = 'goal'\n",
        "# Create a histogram and kernel density estimate (KDE) plot\n",
        "sns.histplot(full_1['goal'], kde=True, bins=30)\n",
        "\n",
        "# Add labels and a title\n",
        "plt.xlabel('Value')\n",
        "plt.ylabel('Frequency')\n",
        "plt.title(f'Distribution of {feature}')\n",
        "\n",
        "# Display the plot\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 573
        },
        "id": "ORNvQn9ZZOLd",
        "outputId": "324624ed-7f0a-4ee2-da13-051af9c8d490"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###pledged"
      ],
      "metadata": {
        "id": "mgaRUc9g2QZO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def feature_eda(feature_name):\n",
        "  print(full_1[feature_name].head())\n",
        "  print()\n",
        "  print()\n",
        "  print(full_1[feature_name].value_counts())\n",
        "  print()\n",
        "  print()\n",
        "  # print(full_1[feature_name].hist())\n",
        "  # # print(full_1.boxplot(column=[feature_name]))\n",
        "  # plt.show()"
      ],
      "metadata": {
        "id": "Vh8xfSp_2Wo6"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('pledged')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 852
        },
        "id": "AZLyqhji2Zrx",
        "outputId": "7064b939-0573-46db-ede8-d9a8159e244b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0      0.0\n",
            "1      0.0\n",
            "2    120.0\n",
            "3      0.0\n",
            "4    356.0\n",
            "Name: pledged, dtype: float64\n",
            "\n",
            "\n",
            "0.00         2936\n",
            "1.00          586\n",
            "10.00         313\n",
            "5.00          199\n",
            "2.00          197\n",
            "             ... \n",
            "3431.00         1\n",
            "26823.01        1\n",
            "196362.57       1\n",
            "212513.64       1\n",
            "1559.00         1\n",
            "Name: pledged, Length: 8722, dtype: int64\n",
            "\n",
            "\n",
            "Axes(0.125,0.11;0.775x0.77)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(full_1.boxplot(column=['pledged']))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 467
        },
        "id": "2wjjQBnZ4kz8",
        "outputId": "cd75c89e-3f2a-4f56-f7ff-3f1aba81f065"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Axes(0.125,0.11;0.775x0.77)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "temp_df = full_1['pledged']\n",
        "\n",
        "from scipy import stats\n",
        "z = np.abs(stats.zscore(temp_df))\n",
        "\n",
        "# Define a threshold (e.g. 3) for identifying outliers\n",
        "threshold = 0.19\n",
        "\n",
        "# Find the indices of the outliers\n",
        "outlier_indices = np.where(z > threshold)\n",
        "\n",
        "# Remove the outliers from the DataFrame\n",
        "df_clean = temp_df.drop(outlier_indices[0], axis=0)\n",
        "df_clean.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "O5cAbxBc89Ws",
        "outputId": "dec1ff42-ab39-40ff-e377-47683ebb43d4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(18890,)"
            ]
          },
          "metadata": {},
          "execution_count": 163
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pd.DataFrame(df_clean).hist()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 474
        },
        "id": "XjO7-h1f9LQp",
        "outputId": "dbad78a6-9de6-4271-a542-17b9bb710c3b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[<Axes: title={'center': 'pledged'}>]], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 164
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###Slug"
      ],
      "metadata": {
        "id": "vVHQDOUgBli6"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('slug')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5mfX9wu2BCcq",
        "outputId": "32ccc4e1-b619-4183-ac18-06e47c7db655"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    auntie-dis-music-time-sign-asl-for-hearing-and...\n",
            "1                      jump-start-kindergarten-toolkit\n",
            "2    ojukwu-balewa-awolowo-oba-public-library-of-ni...\n",
            "3                mastize-mas-tahyz-mas-tahyz-to-spread\n",
            "4    synopse-der-eu-dsgvo-artikel-erwagungsgrunde-bdsg\n",
            "Name: slug, dtype: object\n",
            "\n",
            "\n",
            "auntie-dis-music-time-sign-asl-for-hearing-and-hoh    1\n",
            "jackie-and-the-beanstalk-a-re-spun-yarn               1\n",
            "piq-a-jukebox-for-social-spaces                       1\n",
            "presenting-slacker-a-revolutionary-new-tool           1\n",
            "energybridge-solar-power-grid-tie-and-backup-in-on    1\n",
            "                                                     ..\n",
            "breanna-jean                                          1\n",
            "website-building-app                                  1\n",
            "website-for-parents-of-twins-and-multiples            1\n",
            "annuaire-des-artisans-marocains-sans-moyen-de-mark    1\n",
            "lets-trail-app                                        1\n",
            "Name: slug, Length: 20632, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "currency_trailing_code"
      ],
      "metadata": {
        "id": "i-eqsJqpFqSh"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('currency_trailing_code')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "l15b1aZ-Bo-x",
        "outputId": "d9e2223d-6820-40c2-dad6-0f4598a02e09"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0     True\n",
            "1     True\n",
            "2     True\n",
            "3     True\n",
            "4    False\n",
            "Name: currency_trailing_code, dtype: bool\n",
            "\n",
            "\n",
            "True     16422\n",
            "False     4210\n",
            "Name: currency_trailing_code, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "deadline"
      ],
      "metadata": {
        "id": "8tR-swBCFsN1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('currency_trailing_code')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iTtXexMcFv5a",
        "outputId": "9f78ee27-0378-47ee-ce00-8ccfdf43e81f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0     True\n",
            "1     True\n",
            "2     True\n",
            "3     True\n",
            "4    False\n",
            "Name: currency_trailing_code, dtype: bool\n",
            "\n",
            "\n",
            "True     16422\n",
            "False     4210\n",
            "Name: currency_trailing_code, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('state_changed_at')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CxcHt2aSFyUj",
        "outputId": "fedbe0af-fb08-47e0-b49b-e254910e7b24"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    1/23/2015 10:35\n",
            "1     5/1/2015 16:13\n",
            "2     3/26/2015 8:17\n",
            "3     10/6/2014 0:41\n",
            "4    6/27/2016 12:00\n",
            "Name: state_changed_at, dtype: object\n",
            "\n",
            "\n",
            "12/31/2014 22:59    6\n",
            "3/31/2016 22:59     5\n",
            "8/31/2014 22:59     5\n",
            "6/30/2015 22:59     5\n",
            "9/30/2016 22:59     4\n",
            "                   ..\n",
            "12/9/2015 17:07     1\n",
            "10/31/2016 9:00     1\n",
            "1/1/2015 11:15      1\n",
            "11/28/2015 14:30    1\n",
            "11/20/2014 4:24     1\n",
            "Name: state_changed_at, Length: 20238, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('created_at')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DJoIWmZBF67m",
        "outputId": "4ca6857a-9eb7-4e5a-822b-910bd782a536"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    11/29/2014 22:55\n",
            "1      2/20/2015 9:28\n",
            "2      1/24/2015 0:08\n",
            "3      9/5/2014 22:30\n",
            "4     5/25/2016 14:09\n",
            "Name: created_at, dtype: object\n",
            "\n",
            "\n",
            "2/9/2015 14:08     3\n",
            "9/10/2014 12:47    2\n",
            "7/9/2014 19:17     2\n",
            "5/19/2016 9:58     2\n",
            "5/6/2015 13:37     2\n",
            "                  ..\n",
            "6/9/2015 9:15      1\n",
            "10/1/2015 7:21     1\n",
            "5/11/2016 13:37    1\n",
            "9/30/2016 4:31     1\n",
            "9/28/2014 5:42     1\n",
            "Name: created_at, Length: 20483, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('launched_at')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "anHEw5lhGCp_",
        "outputId": "94f40b1f-9827-41e5-d0cc-4f968104a98f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    12/17/2014 13:47\n",
            "1      3/2/2015 16:13\n",
            "2      1/25/2015 8:17\n",
            "3       9/6/2014 0:41\n",
            "4      5/26/2016 5:57\n",
            "Name: launched_at, dtype: object\n",
            "\n",
            "\n",
            "7/22/2014 11:00     3\n",
            "7/8/2014 12:30      3\n",
            "1/26/2017 11:22     2\n",
            "3/4/2015 15:07      2\n",
            "11/3/2015 9:00      2\n",
            "                   ..\n",
            "6/12/2015 12:03     1\n",
            "12/28/2016 20:35    1\n",
            "3/9/2016 6:41       1\n",
            "10/6/2014 17:31     1\n",
            "10/21/2014 4:24     1\n",
            "Name: launched_at, Length: 20448, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('staff_pick')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "m7HMxWnvGZKY",
        "outputId": "9751b2a6-236f-4ef7-8b27-5f12c2203433"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    False\n",
            "1    False\n",
            "2    False\n",
            "3    False\n",
            "4    False\n",
            "Name: staff_pick, dtype: bool\n",
            "\n",
            "\n",
            "False    18447\n",
            "True      2185\n",
            "Name: staff_pick, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('backers_count')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CE_ekygZGcIZ",
        "outputId": "bea2294c-02e3-407d-89c5-27b4adbdfef9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0     0\n",
            "1     0\n",
            "2     5\n",
            "3     0\n",
            "4    17\n",
            "Name: backers_count, dtype: int64\n",
            "\n",
            "\n",
            "0       2936\n",
            "1       1914\n",
            "2       1276\n",
            "3        910\n",
            "4        714\n",
            "        ... \n",
            "1513       1\n",
            "3863       1\n",
            "2051       1\n",
            "737        1\n",
            "819        1\n",
            "Name: backers_count, Length: 1505, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "full_1['backers_count'].hist()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 451
        },
        "id": "9Es3FS7XGiNs",
        "outputId": "27d94c70-ff15-4b2c-8357-fd026c21a5d7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 181
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "full_1.boxplot(column=['backers_count'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 452
        },
        "id": "XE9Iiwk8HAfA",
        "outputId": "93d614ef-1727-4aa4-b4d8-29a2db8c7350"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 182
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('static_usd_rate')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_iGAnQaPNWz4",
        "outputId": "f7cd8ae8-e8fa-4c66-b540-0f747c50152b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    1.000000\n",
            "1    1.000000\n",
            "2    1.000000\n",
            "3    1.000000\n",
            "4    1.114613\n",
            "Name: static_usd_rate, dtype: float64\n",
            "\n",
            "\n",
            "1.000000    14142\n",
            "1.095020       18\n",
            "1.115888       18\n",
            "1.713370       12\n",
            "1.714466       12\n",
            "            ...  \n",
            "1.418456        1\n",
            "1.375722        1\n",
            "0.116673        1\n",
            "1.088146        1\n",
            "1.000703        1\n",
            "Name: static_usd_rate, Length: 3136, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "full_1.boxplot(column=['static_usd_rate'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 452
        },
        "id": "r6CfRUxNNJhh",
        "outputId": "e38b0c55-9154-4991-fc72-3db2e115ea92"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 183
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "full_1['static_usd_rate'].hist()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 451
        },
        "id": "TiFxMeI8OC__",
        "outputId": "c2c00f02-c1cb-4048-c6be-70d5f3e19a75"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 185
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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BAADa8dfuAQCA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5YUciPbt26f58+dr8uTJyszM1KRJk85Y9/rrr2vChAkaPny4brnlFr377rtBNU1NTSovL9fo0aOVlZWlsrIyHTp0KKhu69atmjp1qkaMGKGxY8equrpahmGYagzDUHV1ta6//nqNGDFCU6dO1bZt20LdPAAAYEEhB6JPPvlEmzZt0uDBg5Wenn7GmrVr1+rhhx9WQUGBampqNHLkSN17771BAWXmzJnasmWLFixYoCeeeEIej0clJSVqa2sL1Ozbt0/FxcVKTk5WVVWVpk+frsrKSq1atco0Vk1NjSorK3XXXXepqqpKycnJKioqUmNjY6ibCAAALKZXqCuMGzdON9xwgyTpwQcf1I4dO4JqKisrNXHiRM2cOVOSNGbMGO3evVsrVqxQTU2NJKm+vl6bN2+Wy+VSXl6eJCk1NVWFhYXasGGDCgsLJUkul0v9+vXTU089JbvdrpycHB0+fFgrV67UHXfcIbvdruPHj6uqqkpFRUW66667JEnXXnutbr75ZrlcLi1YsCDUzQQAABYS8hmimJizr9LY2KiGhgYVFBSYlhcWFqqurk4tLS2SpNraWjmdTuXm5gZq0tLSlJGRodra2sCy2tpajR8/Xna73TSWz+dTfX29pFOX1I4ePWp6TrvdrhtvvNE0FgAAwJmEfIboXNxut6RTZ3tOl56ertbWVjU2Nio9PV1ut1upqamy2WymurS0tMAYzc3N+vzzz5WWlhZUY7PZ5Ha7lZ2dHaj/Zl16erqef/55HTt2TJdeemnI22IYhpqbm89Z5/f7TT+tjF6Y0Y8O3akXNptNDoejq6cRFr/fH3QPZU/XnfaNrkYvzMLph2EYQdnifHR6IPJ6vZIkp9NpWt7+e/vjPp9PCQkJQesnJiYGLsM1NTWdcSy73S6Hw2Eay263Ky4uLug5DcOQ1+sNKxC1trZq165d513f0NAQ8nNEK3phRj86dIdeOBwOZWZmdvU0wuLxeKL2xbI77BvdBb0wC7Ufp19VOl+dHoiiSWxsrIYMGXLOOr/fr4aGBqWkpPTYd52dhV6Y0Y8O3akX4bx77C5SU1Oj8gxRd9k3uhq9MAunH3v27AnruTo9ECUmJko6dXYnOTk5sNzn85kedzqdOnDgQND6Xq83UNN+Bqn9TFG7lpYW+f1+01gtLS06fvy46SyRz+eTzWYL1IXKZrMpPj7+vOsdDkdI9dGMXpjRjw704sJE84sk+0YHemEWSj/CfcPT6V/M2H4fT/t9Pe3cbrdiY2M1aNCgQJ3H4wl6p+PxeAJjxMfH64orrggaq3299rr2nx6PJ+g5BwwYENblMgAAYB2dHogGDRqklJQUrV+/3rR83bp1ysnJCVzXy8/Pl9frVV1dXaDG4/Fo586dys/PDyzLz8/Xxo0b1draahrL6XQqKytLkjRq1Cj16dNHb7/9dqCmtbVVGzZsMI0FAABwJiFfMvP7/dq0aZMkaf/+/Tp69Ggg/IwePVpJSUm67777NGfOHF111VXKzs7WunXrtH37dr300kuBcbKyspSXl6fy8nLNnTtXcXFxWrJkiYYNG6abbropUFdcXKw1a9Zo9uzZmjZtmnbv3i2Xy6VZs2YFwlVcXJxKS0u1bNkyJSUlaejQoXr11Vd15MgRFRcXX1CDAABA9As5EH355Ze6//77Tcvaf3/hhReUnZ2tSZMmye/3q6amRtXV1UpNTdXy5csDZ3TaLV26VIsWLdL8+fPV1tamvLw8zZs3T716dUxr8ODBcrlcWrx4sWbMmKGkpCSVlZWpqKjINFZJSYkMw9CqVat0+PBhZWRkyOVyBS7RAQAAfJuQA9HAgQP18ccfn7NuypQpmjJlyllrEhISVFFRoYqKirPWjRo1SqtXrz5rjc1mU2lpqUpLS885NwAAgNPx1+4BAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlRSwQbdy4UVOmTFFWVpby8vJ0//33q7GxMaju9ddf14QJEzR8+HDdcsstevfdd4NqmpqaVF5ertGjRysrK0tlZWU6dOhQUN3WrVs1depUjRgxQmPHjlV1dbUMw4jI9gEAgOgRkUD0/vvv695779WQIUO0YsUKlZeX6y9/+YuKiop07NixQN3atWv18MMPq6CgQDU1NRo5cqTuvfdebdu2zTTezJkztWXLFi1YsEBPPPGEPB6PSkpK1NbWFqjZt2+fiouLlZycrKqqKk2fPl2VlZVatWpVJDYRAABEkV6RGHTt2rUaMGCAKioqZLPZJElJSUmaPn26duzYoeuuu06SVFlZqYkTJ2rmzJmSpDFjxmj37t1asWKFampqJEn19fXavHmzXC6X8vLyJEmpqakqLCzUhg0bVFhYKElyuVzq16+fnnrqKdntduXk5Ojw4cNauXKl7rjjDtnt9khsKgAAiAIROUPU1tam3r17B8KQJCUkJEhS4BJWY2OjGhoaVFBQYFq3sLBQdXV1amlpkSTV1tbK6XQqNzc3UJOWlqaMjAzV1tYGltXW1mr8+PGm4FNYWCifz6f6+vrO30gAABA1IhKIfvzjH2vv3r16+eWX1dTUpMbGRj311FPKzMzUqFGjJElut1vSqbM9p0tPT1dra2vgfiO3263U1FRTuJJOhaL2MZqbm/X5558rLS0tqMZmswXqAAAAziQil8yuu+46LV++XLNnz9Yvf/lLSVJGRoaeffZZXXLJJZIkr9crSXI6naZ1239vf9zn8wXOLp0uMTFRO3bskHTqpuszjWW32+VwOAJjhcowDDU3N5+zzu/3m35aGb0wox8dulMvbDabHA5HV08jLH6/P+o+LNKd9o2uRi/MwumHYRhBJ1HOR0QC0datW/Vv//Zv+pd/+Rddf/31OnLkiJ5++mnNmDFDr7zyii699NJIPG2na21t1a5du867vqGhIXKT6WHohRn96NAdeuFwOJSZmdnV0wiLx+OJ2hfL7rBvdBf0wizUfoRz33BEAtHChQs1ZswYPfjgg4FlI0eO1PXXX6/f//73mjp1qhITEyWdOruTnJwcqPP5fJIUeNzpdOrAgQNBz+H1egM17WeQ2s8UtWtpaZHf7w/UhSo2NlZDhgw5Z53f71dDQ4NSUlJ67LvOzkIvzOhHh+7Ui3DePXYXqampUXmGqLvsG12NXpiF0489e/aE9VwRCUR79+7V+PHjTcsuv/xy9evXT59++qkkBe73cbvdpnt/3G63YmNjNWjQoEBdXV1d0Ckwj8ejoUOHSpLi4+N1xRVXBN0r5PF4ZBhG0L1F58tmsyk+Pv686x0OR0j10YxemNGPDvTiwkTziyT7Rgd6YRZKP8J9wxORm6oHDBignTt3mpbt379fX331la688kpJ0qBBg5SSkqL169eb6tatW6ecnJzA6a78/Hx5vV7V1dUFajwej3bu3Kn8/PzAsvz8fG3cuFGtra2msZxOp7Kysjp9GwEAQPSIyBmi22+/XRUVFVq4cKHGjRunI0eO6JlnntF3vvMd08fs77vvPs2ZM0dXXXWVsrOztW7dOm3fvl0vvfRSoKb9m67Ly8s1d+5cxcXFacmSJRo2bJhuuummQF1xcbHWrFmj2bNna9q0adq9e7dcLpdmzZrFdxABAICzikgguvPOO2W32/Xqq6/qzTffVO/evTVy5EgtXbpU/fr1C9RNmjRJfr9fNTU1qq6uVmpqqpYvXx50Rmfp0qVatGiR5s+fr7a2NuXl5WnevHnq1atj+oMHD5bL5dLixYs1Y8YMJSUlqaysTEVFRZHYRAAAEEUiEohsNpumTZumadOmnbN2ypQpmjJlyllrEhISVFFRoYqKirPWjRo1SqtXrw5prgAAAPy1ewAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkEIgAAYHkRDUS/+93v9MMf/lDDhw9Xdna2fvrTn+rYsWOBx//whz/olltu0fDhwzVhwgS9+eabQWO0tLToV7/6lXJzczVy5EjdfffdcrvdQXV79+7V3XffrZEjRyo3N1ePP/64WlpaIrl5AAAgSvSK1MDPPPOMampq9LOf/UwjR47UV199pbq6Op04cUKS9Kc//Un33nuvbrvtNpWXl+u9997Tv//7v6t37966+eabA+MsXLhQ69at04MPPqj+/ftr5cqVuuuuu7R27VolJCRIkrxer6ZPn66UlBQtW7ZMBw8e1OLFi3Xs2DHNnz8/UpsIAACiREQCkdvt1vLly/X000/rBz/4QWD5hAkTAv/+zDPPaMSIEfrlL38pSRozZowaGxtVWVkZCEQHDhzQG2+8oUceeUS33XabJGn48OEaO3asXnvtNZWUlEiSXnvtNX399ddavny5+vbtK0k6ceKEHn30UZWWlqp///6R2EwAABAlInLJ7L/+6780cOBAUxg6XUtLi95//33TmSBJKiws1N69e/XZZ59JkjZv3qyTJ0+a6vr27avc3FzV1tYGltXW1ionJycQhiSpoKBAJ0+e1JYtWzpxywAAQDSKyBmiDz/8UEOHDtXTTz+tF198UU1NTfre976nhx56SNdcc40+/fRTtba2Ki0tzbReenq6pFNnmAYOHCi3263vfOc7SkxMDKp74403Ar+73W7deuutphqn06nk5OQz3m90vgzDUHNz8znr/H6/6aeV0Qsz+tGhO/XCZrPJ4XB09TTC4vf7ZRhGV0+jU3WnfaOr0QuzcPphGIZsNlvIzxWRQPTFF19ox44d2r17tx555BE5HA6tXLlSRUVF2rBhg7xer6RToeV07b+3P+7z+QL3CX2zrr2mve6bY0lSYmKiqS5Ura2t2rVr13nXNzQ0hP1c0YZemNGPDt2hFw6HQ5mZmV09jbB4PJ6ofbHsDvtGd0EvzELth91uD/k5IhKI2s+s/Od//qe++93vSpKuueYajRs3Ti+99JLy8vIi8bSdLjY2VkOGDDlnnd/vV0NDg1JSUnrsu87OQi/M6EeH7tSLcN49dhepqalReYaou+wbXY1emIXTjz179oT1XBEJRE6nU3379g2EIenUvT+ZmZnas2ePJk6cKElqamoyrefz+SQpcInM6XTq6NGjQeP7fD7TZTSn0xk0lnTqTNM3L7eFwmazKT4+/rzrHQ5HSPXRjF6Y0Y8O9OLCRPOLJPtGB3phFko/wn3DE5Gbqs92VuX48eO66qqrFBsbG3R/T/vv7fcWpaWl6W9/+1vQZS+32226/ygtLS1orKamJn3xxRdB9ykBAAB8U0QC0dixY3XkyBHT/TdfffWVPvroI1199dWy2+3Kzs7W//zP/5jWW7dundLT0zVw4EBJUl5enmJiYrRhw4ZAjdfr1ebNm5Wfnx9Ylp+frz/+8Y+BM0yStH79esXExCg3NzcSmwgAAKJIRC6Z3XDDDRo+fLjKyso0a9YsxcXFqbq6Wna7XT/5yU8kST//+c915513asGCBSooKND777+vt956S0uWLAmMc/nll+u2227T448/rpiYGPXv319VVVVKSEjQ7bffHqi7/fbb9eKLL+qee+5RaWmpDh48qMcff1y3334730EEAADOKSKBKCYmRtXV1Vq0aJHmz5+v1tZWXXfddXr55ZeVnJwsSbruuuu0bNkyLV26VG+88YYGDBighQsXqqCgwDTWvHnz1Lt3bz355JP6+uuvNWrUKP3mN78xffosMTFRzz//vB577DHdc8896t27t2677TbNmjUrEpsHAACiTMT+dEdSUpJ+/etfn7Vm/PjxGj9+/Flr7Ha75s6dq7lz5561Lj09Xc8991yo0wQAAOCv3QMAABCIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5UU8EH399dfKz8/XsGHD9Oc//9n02Ouvv64JEyZo+PDhuuWWW/Tuu+8Grd/U1KTy8nKNHj1aWVlZKisr06FDh4Lqtm7dqqlTp2rEiBEaO3asqqurZRhGxLYLAABEj4gHoqefflonTpwIWr527Vo9/PDDKigoUE1NjUaOHKl7771X27ZtM9XNnDlTW7Zs0YIFC/TEE0/I4/GopKREbW1tgZp9+/apuLhYycnJqqqq0vTp01VZWalVq1ZFevMAAEAU6BXJwffu3atXXnlFc+fO1SOPPGJ6rLKyUhMnTtTMmTMlSWPGjNHu3bu1YsUK1dTUSJLq6+u1efNmuVwu5eXlSZJSU1NVWFioDRs2qLCwUJLkcrnUr18/PfXUU7Lb7crJydHhw4e1cuVK3XHHHbLb7ZHcTAAA0MNF9AzRwoULdfvttys1NdW0vLGxUQ0NDSooKDAtLywsVF1dnVpaWiRJtbW1cjqdys3NDdSkpaUpIyNDtbW1gWW1tbUaP368KfgUFhbK5/Opvr4+EpsGAACiSMTOEK1fv167d+/WsmXL9NFHH5kec7vdkhQUlNLT09Xa2qrGxkalp6fL7XYrNTVVNpvNVJeWlhYYo7m5WZ9//rnS0tKCamw2m9xut7Kzs8PaBsMw1NzcfM46v99v+mll9MKMfnToTr2w2WxyOBxdPY2w+P3+qLs/sjvtG12NXpiF0w/DMIJyw/mISCDy+/1avHixZs2apT59+gQ97vV6JUlOp9O0vP339sd9Pp8SEhKC1k9MTNSOHTsknbrp+kxj2e12ORyOwFjhaG1t1a5du867vqGhIeznijb0wox+dOgOvXA4HMrMzOzqaYTF4/FE7Ytld9g3ugt6YRZqP8K5VSYigeiZZ57Rd77zHd16662RGP6iiY2N1ZAhQ85Z5/f71dDQoJSUlB77rrOz0Asz+tGhO/UinHeP3UVqampUniHqLvtGV6MXZuH0Y8+ePWE9V6cHov3792vVqlVasWJF4OxN+2Wn5uZmff3110pMTJR06uxOcnJyYF2fzydJgcedTqcOHDgQ9BxerzdQ034Gqf252rW0tMjv9wfqwmGz2RQfH3/e9Q6HI6T6aEYvzOhHB3pxYaL5RZJ9owO9MAulH+G+4en0QPTZZ5+ptbVVM2bMCHrszjvv1DXXXKMnn3xS0ql7iU6/98ftdis2NlaDBg2SdOo+oLq6uqDrgR6PR0OHDpUkxcfH64orrgjcU3R6jWEYQfcWAQAAfFOnf8osIyNDL7zwgumfhx56SJL06KOP6pFHHtGgQYOUkpKi9evXm9Zdt26dcnJyAtf+8vPz5fV6VVdXF6jxeDzauXOn8vPzA8vy8/O1ceNGtba2msZyOp3Kysrq7E0EAABRptPPEDmdzm/9VNfVV1+tq6++WpJ03333ac6cObrqqquUnZ2tdevWafv27XrppZcC9VlZWcrLy1N5ebnmzp2ruLg4LVmyRMOGDdNNN90UqCsuLtaaNWs0e/ZsTZs2Tbt375bL5dKsWbP4DiIAAHBOEf1ixrOZNGmS/H6/ampqVF1drdTUVC1fvjzojM7SpUu1aNEizZ8/X21tbcrLy9O8efPUq1fH1AcPHiyXy6XFixdrxowZSkpKUllZmYqKii72ZgEAgB7oogSi7Oxsffzxx0HLp0yZoilTppx13YSEBFVUVKiiouKsdaNGjdLq1asvaJ4AAMCa+Gv3AADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8iISiN5++239/Oc/V35+vkaOHKnJkyfrjTfekGEYprrXX39dEyZM0PDhw3XLLbfo3XffDRqrqalJ5eXlGj16tLKyslRWVqZDhw4F1W3dulVTp07ViBEjNHbsWFVXVwc9HwAAwJlEJBA999xzcjgcevDBB/XMM88oPz9fDz/8sFasWBGoWbt2rR5++GEVFBSopqZGI0eO1L333qtt27aZxpo5c6a2bNmiBQsW6IknnpDH41FJSYna2toCNfv27VNxcbGSk5NVVVWl6dOnq7KyUqtWrYrE5gEAgCjTKxKDPvPMM0pKSgr8npOToyNHjug3v/mNfvGLXygmJkaVlZWaOHGiZs6cKUkaM2aMdu/erRUrVqimpkaSVF9fr82bN8vlcikvL0+SlJqaqsLCQm3YsEGFhYWSJJfLpX79+umpp56S3W5XTk6ODh8+rJUrV+qOO+6Q3W6PxGYCAIAoEZEzRKeHoXYZGRk6evSompub1djYqIaGBhUUFJhqCgsLVVdXp5aWFklSbW2tnE6ncnNzAzVpaWnKyMhQbW1tYFltba3Gjx9vCj6FhYXy+Xyqr6/v7M0DAABRJiJniM7kgw8+UP/+/dWnTx998MEHkk6d7Tldenq6Wltb1djYqPT0dLndbqWmpspms5nq0tLS5Ha7JUnNzc36/PPPlZaWFlRjs9nkdruVnZ0d1pwNw1Bzc/M56/x+v+mnldELM/rRoTv1wmazyeFwdPU0wuL3+6Pu/sjutG90NXphFk4/DMMIyg3n46IEoj/96U9at26d5s6dK0nyer2SJKfTaapr/739cZ/Pp4SEhKDxEhMTtWPHDkmnbro+01h2u10OhyMwVjhaW1u1a9eu865vaGgI+7miDb0wox8dukMvHA6HMjMzu3oaYfF4PFH7Ytkd9o3ugl6YhdqPcG6ViXggOnDggGbNmqXs7GzdeeedkX66ThUbG6shQ4acs87v96uhoUEpKSk99l1nZ6EXZvSjQ3fqRTjvHruL1NTUqDxD1F32ja5GL8zC6ceePXvCeq6IBiKfz6eSkhL17dtXy5YtU0zMqVuWEhMTJZ06u5OcnGyqP/1xp9OpAwcOBI3r9XoDNe1nkNrPFLVraWmR3+8P1IXDZrMpPj7+vOsdDkdI9dGMXpjRjw704sJE84sk+0YHemEWSj/CfcMTsS9mPHbsmEpLS9XU1KRnn33WdOmr/X6f9vuA2rndbsXGxmrQoEGBOo/HE/RuyOPxBMaIj4/XFVdcETRW+3rfvLcIAADgmyISiNra2jRz5ky53W49++yz6t+/v+nxQYMGKSUlRevXrzctX7dunXJycgLX/vLz8+X1elVXVxeo8Xg82rlzp/Lz8wPL8vPztXHjRrW2tprGcjqdysrKisQmAgCAKBKRS2aPPvqo3n33XT344IM6evSo6csWMzMzZbfbdd9992nOnDm66qqrlJ2drXXr1mn79u166aWXArVZWVnKy8tTeXm55s6dq7i4OC1ZskTDhg3TTTfdFKgrLi7WmjVrNHv2bE2bNk27d++Wy+XSrFmz+A4iAABwThEJRFu2bJEkLV68OOixjRs3auDAgZo0aZL8fr9qampUXV2t1NRULV++POiMztKlS7Vo0SLNnz9fbW1tysvL07x589SrV8fUBw8eLJfLpcWLF2vGjBlKSkpSWVmZioqKIrF5AAAgykQkEP3hD384r7opU6ZoypQpZ61JSEhQRUWFKioqzlo3atQorV69+rznCAAA0I6/dg8AACyPQAQAACyPQAQAACyPQAQAACyPQAQAPUDfhDidPNkz/2RHT503rOWi/bV7AED4+jhiFRNj0xMvf6DPDjade4VuYmD/BM3512u7ehrAORGIAKAH+exgk/bu93b1NICowyUzABeFzWaTw+Ho0X9pHkD04gwRgAt28qShmJizBx2Hw6HMzMyLNCMACA2BCMAF62n3toz67mW6s5BwBqADgQhAp+hJ97YMvKxPV08BQDfDPUQAAMDyCEQAAHQTfPig63DJDACAbzifDwpEwoV8+ODESUOXdMGcL0RX9flMCEQAAHxDT/2gQE+ac3f70k4CEQAAZ9ATPyjQk+bc3XAPEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQCgS9lsNjkcDtlstq6eCiysV1dPwKpOnjQUE9Oz/ufviXMG0LX6JsSd89jhcDiUmZl5EWcFBCMQdZGYGJueePkDfXawqauncl4G9k/QnH+9tqunAaCH6eOI7XHHu1HfvUx3FhLQrIZA1IU+O9ikvfu9XT0NAIi4nnS8G3hZn66eAroA9xABAADLi6pAtHfvXt19990aOXKkcnNz9fjjj6ulpaWrpwUAALq5qLlk5vV6NX36dKWkpGjZsmU6ePCgFi9erGPHjmn+/PldPT0AANCNRU0geu211/T1119r+fLl6tu3ryTpxIkTevTRR1VaWqr+/ft37QSB88Sn+QDg4ouaQFRbW6ucnJxAGJKkgoICPfLII9qyZYt+/OMfd93kgBDwiRwAuPhshmEYXT2JzpCTk6Nbb71Vc+bMMS3/f//v/2ny5MlBy89l69atMgxDsbGx56w1DENtbW3q1avXeX+xmM1mk/doi9pOnAxpXl2l1yUxSuxj17l2F8MwdOLECV1yySV8yZrC60dP2zfiYi9Rn/hY5hxhPXHOUs+cN3O+OM7ndSWc19fW1lbZbDaNGjUqtPmEVN2N+Xw+OZ3OoOWJiYnyekP/qGd748/nP4DNZpPdbg/5ORL7hL5OVztXP2w2m2Jioupe/QsSbj964r7BnC+OnjhnqWfOmzlfHGd7XQnn9dVms4X1hjxqAlFny8rK6uopAACAiyRq3so7nU41NQXfc+H1epWYmNgFMwIAAD1F1ASitLQ0ud1u07KmpiZ98cUXSktL66JZAQCAniBqAlF+fr7++Mc/yufzBZatX79eMTExys3N7cKZAQCA7i5qPmXm9Xo1ceJEpaamqrS0NPDFjP/8z//MFzMCAICzippAJJ360x2PPfaY6uvr1bt3b02ePFmzZs0K6xNgAADAOqIqEAEAAIQjau4hAgAACBeBCAAAWB6BCAAAWB6BCAAAWB6BCAAAWB6BCAAAWB5/3PU0e/fu1cKFC03fYzRz5sxzfo+RYRiqqanRK6+8osOHDysjI0MPPfSQRo4caao7ePCgFi5cqM2bNys2NlY33nijHnroIfXp0yeCWxWecHpx6NAhPffcc9qyZYs+/fRTJSQk6Pvf/74eeOABXXnllYG6999/X3feeWfQ+oWFhVqyZElEtudChbtvjBs3Tvv37w9avn37dsXFxQV+j/Z949v+m0tSamqq1q9ff9a67rpv7Nu3Ty6XSx9++KE++eQTpaWl6a233jrnetF4zJDC60e0HjfC3Tei8ZghhdePi33cIBD9ndfr1fTp05WSkqJly5YFvun62LFj5/ym65qaGlVWVmrOnDkaNmyYXn75ZRUVFen3v/+9Bg0aJElqbW3VT3/6U0nSk08+qWPHjulXv/qVZs+eraqqqohvXyjC7cVHH32kd955R7feequuueYaffXVV3rmmWc0ZcoUvfXWW0pKSjLVL1q0yPR35vr16xexbboQF7JvSNKECRNUVFRkWnZ6eLDCvnH11Vfrt7/9rWnZ0aNHVVJSovz8/KD6nrJvfPLJJ9q0aZOuueYanTx5Uuf7tW7RdsxoF04/ovW4Ee6+IUXXMaNdOP246McNA4ZhGMbKlSuNkSNHGl999VVg2WuvvWZkZGQYBw4c+Nb1jh07ZowaNcp48sknA8uOHz9ujB071njkkUcCy9asWWMMGzbM2Lt3b2DZ//3f/xlDhw41Pvzww07dlgsVbi+8Xq/R2tpqWvb5558bw4YNM1wuV2DZe++9ZwwdOtTYvn17p889EsLth2EYxtixY41HH330rDVW2DfO5M033wzaxp62b5w4cSLw73PnzjUmTpx4znWi8ZjRLpx+ROtxI5xeGEb0HTPahduPb4rkcYN7iP6utrZWOTk56tu3b2BZQUGBTp48qS1btnzrelu3btXRo0dVUFAQWGa323XjjTeqtrbWNP6wYcNM6TU3N1d9+/bVpk2bOndjLlC4vXA6nerVy3zS8fLLL1dSUpIOHToUqelGXLj9CGX8aN83zuStt95SSkqKRowY0cmzvHhiYkI/hEbjMaNdOP2I1uNGOL04X1bZN84kkscNAtHfud1u084lnfofNTk5WW63+6zrSQpaNz09XX/961917Nixbx3fZrMpNTX1rON3hXB7cSYej0dffvml0tPTgx6bMWOGMjIylJ+fr1/96leBXnU3F9qPNWvW6Hvf+56ysrJUUlKijz/++JzjR/u+8be//U3vvfeeJk2adMbHe8q+EY5oPGZ0tmg4blyIaDpmdKZIHze4h+jvfD6fnE5n0PLExER5vd6zrme32003u0mnXiQMw5DX69Wll14qn8+nhISEkMfvCuH24psMw9DChQt12WWXaeLEiYHlCQkJ+ulPf6rvf//7iouL03vvvadVq1bJ7XZ3y+vfF9KPcePGacSIERowYIAaGxu1cuVK/eQnP9F///d/B+4VseK+sW7dOp04cSLowNbT9o1wROMxozNFy3EjXNF2zOhMkT5uEIgQMcuWLdN7772nZ599VvHx8YHlmZmZyszMDPyek5Ojyy67TL/85S+1ffv2Hn0J5ZvmzZsX+PfrrrtOubm5KigokMvl0oIFC7puYl1szZo1uvrqq5WammpabqV9A2dm9eMGx4xvF+njBpfM/s7pdKqpqSloudfrVWJi4lnXa2lp0fHjx03LfT6fbDZbYF2n06mjR4+GPH5XCLcXp1u9erVWrFihRx99VDk5Oeesb7+fYseOHaFN9iLojH60u+yyy3Tttdfqo48+Mo1vpX3j008/1fbt23XLLbecV3133jfCEY3HjM4STceNztLTjxmd5WIcNwhEf5eWlhZ07bWpqUlffPFF0LXab64nnbrmfTq3260BAwbo0ksv/dbxDcOQx+M56/hdIdxetHvnnXe0YMEClZWV6bbbbovUNC+aC+1HOONH674hnXqXFxMTo8LCwkhMsduLxmNGZ4i240YkWW3fkC7OcYNA9Hf5+fn64x//KJ/PF1i2fv16xcTEKDc391vXGzVqlPr06aO33347sKy1tVUbNmwwfU9Cfn6+/vKXv6ihoSGwrK6uTkeOHNEPfvCDzt2YCxRuL6RTX5D1wAMPaMqUKbrnnnvO+znXrl0rSRo+fHh4k46gC+nHNx08eFAffPCBaTutsm+0W7t2rUaPHq3LLrvsvOul7rlvhCMajxkXKhqPG52lpx8zOsvFOG5wD9Hf3X777XrxxRd1zz33qLS0VAcPHtTjjz+u22+/Xf379w/UTZ8+XX/961/1zjvvSJLi4uJUWlqqZcuWKSkpSUOHDtWrr76qI0eOqLi4OLDehAkTVFVVpfvuu08PPPCA/H6/Hn/8cV1//fXd7tp3uL3Yu3ev7rnnHqWkpGjy5Mnatm1boDYpKUlXXXWVJGnOnDkaPHiwMjMzAzfAPffcc7rhhhu65YEt3H689dZbevfdd/WDH/xAl112mRobG1VdXa1LLrlEd999d2A9K+wb7Xbu3Km9e/eatv90PW3f8Pv9gY8579+/X0ePHg18e+7o0aOVlJRkiWNGu3D6Ea3HjXB6EY3HjHbh9KPdxTpuEIj+LjExUc8//7wee+wx3XPPPerdu7duu+02zZo1y1R38uRJnThxwrSspKREhmFo1apVga/hd7lcgU8ESFJsbKyeffZZLVy4UA888IB69eqlG2+8UeXl5Rdl+0IRbi8+/PBDNTU1qampSdOmTTPV/uhHP9LixYslSf/4j/+oNWvWaNWqVWptbdWVV16pn/3sZ5oxY0bkNy4M4fZj4MCBOnTokCoqKtTU1KSEhASNGTNGZWVllts32q1Zs0Z2u10TJkw44/g9bd/48ssvdf/995uWtf/+wgsvKDs72xLHjHbh9CNajxvh9CIajxntwv1/Rbp4xw2bYYTwfeIAAABRiHuIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5RGIAACA5f1/XsRrdmBfe5wAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('usd_pledged')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fyWL-ju2OKJO",
        "outputId": "80214a17-9ff1-41b7-ec2e-fc1f8f4ff810"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0      0.000000\n",
            "1      0.000000\n",
            "2    120.000000\n",
            "3      0.000000\n",
            "4    396.802395\n",
            "Name: usd_pledged, dtype: float64\n",
            "\n",
            "\n",
            "0.000000        2936\n",
            "1.000000         364\n",
            "10.000000        192\n",
            "25.000000        149\n",
            "50.000000        137\n",
            "                ... \n",
            "58.068995          1\n",
            "3427.000000        1\n",
            "2201.677381        1\n",
            "54681.000000       1\n",
            "485.123930         1\n",
            "Name: usd_pledged, Length: 12235, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "full_1['usd_pledged'].hist()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 470
        },
        "id": "Cc_oDOmtOPUL",
        "outputId": "bfb619e4-3c48-44ed-8521-d21643904427"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 187
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "full_1.boxplot(column=['usd_pledged'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 469
        },
        "id": "-pwBRqd8OgvK",
        "outputId": "53ff41b1-5e31-43c6-ecca-98326367672a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 188
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('creator')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0ku2-dx4OqkD",
        "outputId": "b649eb3d-30cb-4458-aa91-87e38dc29a27"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    {\"urls\":{\"web\":{\"user\":\"https://www.kickstarte...\n",
            "1    {\"urls\":{\"web\":{\"user\":\"https://www.kickstarte...\n",
            "2    {\"urls\":{\"web\":{\"user\":\"https://www.kickstarte...\n",
            "3    {\"urls\":{\"web\":{\"user\":\"https://www.kickstarte...\n",
            "4    {\"urls\":{\"web\":{\"user\":\"https://www.kickstarte...\n",
            "Name: creator, dtype: object\n",
            "\n",
            "\n",
            "{\"urls\":{\"web\":{\"user\":\"https://www.kickstarter.com/profile/land-boards\"},\"api\":{\"user\":\"https://api.kickstarter.com/v1/users/1546666383?signature=1487284882.82aacc6a0d3bf326d3c618d1ee189124e47abd20\"}},\"name\":\"Doug Gilliland\",\"id\":1546666383,\"avatar\":{\"small\":\"https://ksr-ugc.imgix.net/assets/008/926/025/c888de15946bd3091a62450d5a68f02d_original.JPG?w=160&h=160&fit=crop&v=1480788385&auto=format&q=92&s=80b39e279ecc9afd0596690303dd0261\",\"thumb\":\"https://ksr-ugc.imgix.net/assets/008/926/025/c888de15946bd3091a62450d5a68f02d_original.JPG?w=40&h=40&fit=crop&v=1480788385&auto=format&q=92&s=652b8b0b15352109bee31c6451962acf\",\"medium\":\"https://ksr-ugc.imgix.net/assets/008/926/025/c888de15946bd3091a62450d5a68f02d_original.JPG?w=160&h=160&fit=crop&v=1480788385&auto=format&q=92&s=80b39e279ecc9afd0596690303dd0261\"},\"slug\":\"land-boards\"}    5\n",
            "{\"urls\":{\"web\":{\"user\":\"https://www.kickstarter.com/profile/249225636\"},\"api\":{\"user\":\"https://api.kickstarter.com/v1/users/249225636?signature=1487284909.b09126a1704231dde1b5a933f8bbaafe735a1cb8\"}},\"name\":\"Isaac Porras\",\"id\":249225636,\"avatar\":{\"small\":\"https://ksr-ugc.imgix.net/assets/006/140/208/a40db92224c9a9e6ffc6607063c78261_original.JPG?w=160&h=160&fit=crop&v=1461369119&auto=format&q=92&s=0284be106984899e74e665b24578088e\",\"thumb\":\"https://ksr-ugc.imgix.net/assets/006/140/208/a40db92224c9a9e6ffc6607063c78261_original.JPG?w=40&h=40&fit=crop&v=1461369119&auto=format&q=92&s=959af00aa3ca6b7ea2ca72c850a4c4ef\",\"medium\":\"https://ksr-ugc.imgix.net/assets/006/140/208/a40db92224c9a9e6ffc6607063c78261_original.JPG?w=160&h=160&fit=crop&v=1461369119&auto=format&q=92&s=0284be106984899e74e665b24578088e\"}}                               3\n",
            "{\"urls\":{\"web\":{\"user\":\"https://www.kickstarter.com/profile/programming\"},\"api\":{\"user\":\"https://api.kickstarter.com/v1/users/1006319399?signature=1487284261.76cb5eebfbb22fecf562a5c5c541e2f6ae0f0290\"}},\"name\":\"Ivelin Demirov\",\"id\":1006319399,\"avatar\":{\"small\":\"https://ksr-ugc.imgix.net/assets/007/593/076/519ab40422060499601cc36f119e246d_original.jpg?w=160&h=160&fit=crop&v=1469111132&auto=format&q=92&s=1ffcbc1249b63288d2131220dd4486bf\",\"thumb\":\"https://ksr-ugc.imgix.net/assets/007/593/076/519ab40422060499601cc36f119e246d_original.jpg?w=40&h=40&fit=crop&v=1469111132&auto=format&q=92&s=d153e6685ec7cc53a923e3a5a7ec541e\",\"medium\":\"https://ksr-ugc.imgix.net/assets/007/593/076/519ab40422060499601cc36f119e246d_original.jpg?w=160&h=160&fit=crop&v=1469111132&auto=format&q=92&s=1ffcbc1249b63288d2131220dd4486bf\"},\"slug\":\"programming\"}    3\n",
            "{\"urls\":{\"web\":{\"user\":\"https://www.kickstarter.com/profile/143072809\"},\"api\":{\"user\":\"https://api.kickstarter.com/v1/users/143072809?signature=1487284503.1eb4055c393668289dce9b957e23547a01d94987\"}},\"name\":\"Brian Jepson\",\"id\":143072809,\"avatar\":{\"small\":\"https://ksr-ugc.imgix.net/assets/005/807/730/cdcc8d58967d910edbe70884e53d853e_original.jpeg?w=160&h=160&fit=crop&v=1461086538&auto=format&q=92&s=0146465317d7743b443015c904fa0dff\",\"thumb\":\"https://ksr-ugc.imgix.net/assets/005/807/730/cdcc8d58967d910edbe70884e53d853e_original.jpeg?w=40&h=40&fit=crop&v=1461086538&auto=format&q=92&s=d03abb02c18718e0ad92650493068606\",\"medium\":\"https://ksr-ugc.imgix.net/assets/005/807/730/cdcc8d58967d910edbe70884e53d853e_original.jpeg?w=160&h=160&fit=crop&v=1461086538&auto=format&q=92&s=0146465317d7743b443015c904fa0dff\"}}                            3\n",
            "{\"urls\":{\"web\":{\"user\":\"https://www.kickstarter.com/profile/155208900\"},\"api\":{\"user\":\"https://api.kickstarter.com/v1/users/155208900?signature=1487284889.1649c5d7a6726f7331e53c050e209c5b750f336b\"}},\"name\":\"john buckovetz\",\"id\":155208900,\"avatar\":{\"small\":\"https://ksr-ugc.imgix.net/assets/010/525/302/5a347958195bd02727ac31bfaa015ebf_original.png?w=160&h=160&fit=crop&v=1461695594&auto=format&q=92&s=3bcf190bcb1cd8c79be9c9801839438d\",\"thumb\":\"https://ksr-ugc.imgix.net/assets/010/525/302/5a347958195bd02727ac31bfaa015ebf_original.png?w=40&h=40&fit=crop&v=1461695594&auto=format&q=92&s=0ae0347dfc098bbabb554e9c59530f5f\",\"medium\":\"https://ksr-ugc.imgix.net/assets/010/525/302/5a347958195bd02727ac31bfaa015ebf_original.png?w=160&h=160&fit=crop&v=1461695594&auto=format&q=92&s=3bcf190bcb1cd8c79be9c9801839438d\"}}                             3\n",
            "                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     ..\n",
            "{\"urls\":{\"web\":{\"user\":\"https://www.kickstarter.com/profile/homeloansforall\"},\"api\":{\"user\":\"https://api.kickstarter.com/v1/users/1238771276?signature=1487284115.dfb9662d8ce7e12917429052227538567fc87d26\"}},\"name\":\"Randy A. (deleted)\",\"id\":1238771276,\"avatar\":{\"small\":\"https://ksr-ugc.imgix.net/missing_user_avatar.png?w=160&h=160&fit=crop&v=&auto=format&q=92&s=c40e6ddb23a144ee8beca514ec2d6e58\",\"thumb\":\"https://ksr-ugc.imgix.net/missing_user_avatar.png?w=40&h=40&fit=crop&v=&auto=format&q=92&s=8c0db61c92692000c2678b375fc31714\",\"medium\":\"https://ksr-ugc.imgix.net/missing_user_avatar.png?w=160&h=160&fit=crop&v=&auto=format&q=92&s=c40e6ddb23a144ee8beca514ec2d6e58\"},\"slug\":\"homeloansforall\"}                                                                                                                                                 1\n",
            "{\"urls\":{\"web\":{\"user\":\"https://www.kickstarter.com/profile/1401719656\"},\"api\":{\"user\":\"https://api.kickstarter.com/v1/users/1401719656?signature=1487284115.413090991f357b97d8e279c9c6d083e37a78b8aa\"}},\"name\":\"Gordon\",\"id\":1401719656,\"avatar\":{\"small\":\"https://ksr-ugc.imgix.net/assets/009/126/558/256d61334807754dd1c4373f66e5148a_original.JPG?w=160&h=160&fit=crop&v=1461559480&auto=format&q=92&s=213ddd5793e77a9d57dae28c0bc7e49e\",\"thumb\":\"https://ksr-ugc.imgix.net/assets/009/126/558/256d61334807754dd1c4373f66e5148a_original.JPG?w=40&h=40&fit=crop&v=1461559480&auto=format&q=92&s=f1639376e330101673341ed7469fef6f\",\"medium\":\"https://ksr-ugc.imgix.net/assets/009/126/558/256d61334807754dd1c4373f66e5148a_original.JPG?w=160&h=160&fit=crop&v=1461559480&auto=format&q=92&s=213ddd5793e77a9d57dae28c0bc7e49e\"}}                                  1\n",
            "{\"urls\":{\"web\":{\"user\":\"https://www.kickstarter.com/profile/1469191865\"},\"api\":{\"user\":\"https://api.kickstarter.com/v1/users/1469191865?signature=1487284115.b93a2179db2e38d419c84b3c5b8068a1a3f475f5\"}},\"name\":\"Daniel Hood\",\"id\":1469191865,\"avatar\":{\"small\":\"https://ksr-ugc.imgix.net/assets/009/983/395/df61bf34f2b6dcd8c1dc9fa680fbca1a_original.jpg?w=160&h=160&fit=crop&v=1461657458&auto=format&q=92&s=3cf8d46c687a4bae6a5ab7f8e93a754b\",\"thumb\":\"https://ksr-ugc.imgix.net/assets/009/983/395/df61bf34f2b6dcd8c1dc9fa680fbca1a_original.jpg?w=40&h=40&fit=crop&v=1461657458&auto=format&q=92&s=b66beebd8c16e2bfe4628579f7b4f0b9\",\"medium\":\"https://ksr-ugc.imgix.net/assets/009/983/395/df61bf34f2b6dcd8c1dc9fa680fbca1a_original.jpg?w=160&h=160&fit=crop&v=1461657458&auto=format&q=92&s=3cf8d46c687a4bae6a5ab7f8e93a754b\"}}                             1\n",
            "{\"urls\":{\"web\":{\"user\":\"https://www.kickstarter.com/profile/1499759241\"},\"api\":{\"user\":\"https://api.kickstarter.com/v1/users/1499759241?signature=1487284115.2e5444e91cc880fe5ecbc2686a8263711e36edd9\"}},\"name\":\"Ricardo Choi Ro\",\"id\":1499759241,\"avatar\":{\"small\":\"https://ksr-ugc.imgix.net/assets/013/167/731/aa62b9ec280bd5d0ab1ec6daa7f5477a_original.jpg?w=160&h=160&fit=crop&v=1469463405&auto=format&q=92&s=20384e9d52210eaa97396f846628fe45\",\"thumb\":\"https://ksr-ugc.imgix.net/assets/013/167/731/aa62b9ec280bd5d0ab1ec6daa7f5477a_original.jpg?w=40&h=40&fit=crop&v=1469463405&auto=format&q=92&s=9c6c3a14152f8f66ddc0cd0720de018e\",\"medium\":\"https://ksr-ugc.imgix.net/assets/013/167/731/aa62b9ec280bd5d0ab1ec6daa7f5477a_original.jpg?w=160&h=160&fit=crop&v=1469463405&auto=format&q=92&s=20384e9d52210eaa97396f846628fe45\"}}                         1\n",
            "{\"urls\":{\"web\":{\"user\":\"https://www.kickstarter.com/profile/1857230317\"},\"api\":{\"user\":\"https://api.kickstarter.com/v1/users/1857230317?signature=1487284996.a24b80731ebf45186781467bbba2c09f5ca846a9\"}},\"name\":\"Fiona O Doherty\",\"id\":1857230317,\"avatar\":{\"small\":\"https://ksr-ugc.imgix.net/assets/009/286/039/d593ee6793a0a6b845b5413056f4f353_original.jpg?w=160&h=160&fit=crop&v=1461574117&auto=format&q=92&s=5feeacdaf64687a8dbc0e94bc646394d\",\"thumb\":\"https://ksr-ugc.imgix.net/assets/009/286/039/d593ee6793a0a6b845b5413056f4f353_original.jpg?w=40&h=40&fit=crop&v=1461574117&auto=format&q=92&s=f9aea7d46994c5f5457125382d990e99\",\"medium\":\"https://ksr-ugc.imgix.net/assets/009/286/039/d593ee6793a0a6b845b5413056f4f353_original.jpg?w=160&h=160&fit=crop&v=1461574117&auto=format&q=92&s=5feeacdaf64687a8dbc0e94bc646394d\"}}                         1\n",
            "Name: creator, Length: 20522, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('location')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8PiNEOjMY8CT",
        "outputId": "0d6ab2a2-1791-4829-ebba-aaaca7bbb97d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    {\"country\":\"US\",\"urls\":{\"web\":{\"discover\":\"htt...\n",
            "1    {\"country\":\"US\",\"urls\":{\"web\":{\"discover\":\"htt...\n",
            "2    {\"country\":\"NG\",\"urls\":{\"web\":{\"discover\":\"htt...\n",
            "3    {\"country\":\"US\",\"urls\":{\"web\":{\"discover\":\"htt...\n",
            "4    {\"country\":\"DE\",\"urls\":{\"web\":{\"discover\":\"htt...\n",
            "Name: location, dtype: object\n",
            "\n",
            "\n",
            "{\"country\":\"GB\",\"urls\":{\"web\":{\"discover\":\"https://www.kickstarter.com/discover/places/london-gb\",\"location\":\"https://www.kickstarter.com/locations/london-gb\"},\"api\":{\"nearby_projects\":\"https://api.kickstarter.com/v1/discover?signature=1487275935.3fd1a29e3904e654fda33e02590c3487346a5be6&woe_id=44418\"}},\"name\":\"London\",\"displayable_name\":\"London, UK\",\"short_name\":\"London, UK\",\"id\":44418,\"state\":\"England\",\"type\":\"Town\",\"is_root\":false,\"slug\":\"london-gb\"}                                                                                           550\n",
            "{\"country\":\"US\",\"urls\":{\"web\":{\"discover\":\"https://www.kickstarter.com/discover/places/new-york-ny\",\"location\":\"https://www.kickstarter.com/locations/new-york-ny\"},\"api\":{\"nearby_projects\":\"https://api.kickstarter.com/v1/discover?signature=1487275939.b1a505f359634dc0bd1c28204ff26762b0d8d902&woe_id=2459115\"}},\"name\":\"New York\",\"displayable_name\":\"New York, NY\",\"short_name\":\"New York, NY\",\"id\":2459115,\"state\":\"NY\",\"type\":\"Town\",\"is_root\":false,\"slug\":\"new-york-ny\"}                                                                                471\n",
            "{\"country\":\"US\",\"urls\":{\"web\":{\"discover\":\"https://www.kickstarter.com/discover/places/los-angeles-ca\",\"location\":\"https://www.kickstarter.com/locations/los-angeles-ca\"},\"api\":{\"nearby_projects\":\"https://api.kickstarter.com/v1/discover?signature=1487284342.729f734403b8671479e32323ba78ade27c0bafd3&woe_id=2442047\"}},\"name\":\"Los Angeles\",\"displayable_name\":\"Los Angeles, CA\",\"short_name\":\"Los Angeles, CA\",\"id\":2442047,\"state\":\"CA\",\"type\":\"Town\",\"is_root\":false,\"slug\":\"los-angeles-ca\"}                                                              334\n",
            "{\"country\":\"GB\",\"urls\":{\"web\":{\"discover\":\"https://www.kickstarter.com/discover/places/london-gb\",\"location\":\"https://www.kickstarter.com/locations/london-gb\"},\"api\":{\"nearby_projects\":\"https://api.kickstarter.com/v1/discover?signature=1487284344.62bb2c371f9fabb9c0015327716bf21a466ac781&woe_id=44418\"}},\"name\":\"London\",\"displayable_name\":\"London, UK\",\"short_name\":\"London, UK\",\"id\":44418,\"state\":\"England\",\"type\":\"Town\",\"is_root\":false,\"slug\":\"london-gb\"}                                                                                           299\n",
            "{\"country\":\"US\",\"urls\":{\"web\":{\"discover\":\"https://www.kickstarter.com/discover/places/los-angeles-ca\",\"location\":\"https://www.kickstarter.com/locations/los-angeles-ca\"},\"api\":{\"nearby_projects\":\"https://api.kickstarter.com/v1/discover?signature=1487275937.c9411d19851f5f05714eda28ba8c0ba94d92bfa6&woe_id=2442047\"}},\"name\":\"Los Angeles\",\"displayable_name\":\"Los Angeles, CA\",\"short_name\":\"Los Angeles, CA\",\"id\":2442047,\"state\":\"CA\",\"type\":\"Town\",\"is_root\":false,\"slug\":\"los-angeles-ca\"}                                                              293\n",
            "                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  ... \n",
            "{\"country\":\"FR\",\"urls\":{\"web\":{\"discover\":\"https://www.kickstarter.com/discover/places/vesoul-upper-saone-fr\",\"location\":\"https://www.kickstarter.com/locations/vesoul-upper-saone-fr\"},\"api\":{\"nearby_projects\":\"https://api.kickstarter.com/v1/discover?signature=1487280740.10deb924a90794ef4488705fec17ef44b56871fb&woe_id=12654258\"}},\"name\":\"Vesoul\",\"displayable_name\":\"Vesoul, France\",\"short_name\":\"Vesoul, France\",\"id\":12654258,\"state\":\"Franche-Comte\",\"type\":\"LocalAdmin\",\"is_root\":false,\"slug\":\"vesoul-upper-saone-fr\"}                               1\n",
            "{\"country\":\"US\",\"urls\":{\"web\":{\"discover\":\"https://www.kickstarter.com/discover/places/mckeesport-pa\",\"location\":\"https://www.kickstarter.com/locations/mckeesport-pa\"},\"api\":{\"nearby_projects\":\"https://api.kickstarter.com/v1/discover?signature=1487275986.d7fffabd89fe35abedba82f936cd38f8ce8573d9&woe_id=2448119\"}},\"name\":\"Mckeesport\",\"displayable_name\":\"Mckeesport, PA\",\"short_name\":\"Mckeesport, PA\",\"id\":2448119,\"state\":\"PA\",\"type\":\"Town\",\"is_root\":false,\"slug\":\"mckeesport-pa\"}                                                                      1\n",
            "{\"country\":\"US\",\"urls\":{\"web\":{\"discover\":\"https://www.kickstarter.com/discover/places/uniontown-belmont-oh\",\"location\":\"https://www.kickstarter.com/locations/uniontown-belmont-oh\"},\"api\":{\"nearby_projects\":\"https://api.kickstarter.com/v1/discover?signature=1487278143.e052877846bd49731b1ab6178abf232a6412e9b1&woe_id=2509958\"}},\"name\":\"Uniontown\",\"displayable_name\":\"Uniontown, OH\",\"short_name\":\"Uniontown, OH\",\"id\":2509958,\"state\":\"OH\",\"type\":\"Town\",\"is_root\":false,\"slug\":\"uniontown-belmont-oh\"}                                                    1\n",
            "{\"country\":\"NL\",\"urls\":{\"web\":{\"discover\":\"https://www.kickstarter.com/discover/places/hilversum-nl\",\"location\":\"https://www.kickstarter.com/locations/hilversum-nl\"},\"api\":{\"nearby_projects\":\"https://api.kickstarter.com/v1/discover?signature=1487275964.e698dec8ee2568fcc22a3325418da6ceea708aa2&woe_id=730138\"}},\"name\":\"Hilversum\",\"displayable_name\":\"Hilversum, Netherlands\",\"short_name\":\"Hilversum, Netherlands\",\"id\":730138,\"state\":\"North Holland\",\"type\":\"Town\",\"is_root\":false,\"slug\":\"hilversum-nl\"}                                                 1\n",
            "{\"country\":\"DE\",\"urls\":{\"web\":{\"discover\":\"https://www.kickstarter.com/discover/places/ebersberg-gemeinde-ebersberg-de\",\"location\":\"https://www.kickstarter.com/locations/ebersberg-gemeinde-ebersberg-de\"},\"api\":{\"nearby_projects\":\"https://api.kickstarter.com/v1/discover?signature=1487284996.7e880875165e00c91865061e40f32a22dd75f854&woe_id=646245\"}},\"name\":\"Ebersberg\",\"displayable_name\":\"Ebersberg, Germany\",\"short_name\":\"Ebersberg, Germany\",\"id\":646245,\"state\":\"Bavaria\",\"type\":\"Town\",\"is_root\":false,\"slug\":\"ebersberg-gemeinde-ebersberg-de\"}      1\n",
            "Name: location, Length: 5178, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('category')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xVPZfYKZatOM",
        "outputId": "c68c5131-2d92-4aec-98d9-1c74bc23a62d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    Academic\n",
            "1    Academic\n",
            "2    Academic\n",
            "3    Academic\n",
            "4    Academic\n",
            "Name: category, dtype: object\n",
            "\n",
            "\n",
            "Web             3325\n",
            "Hardware        3248\n",
            "Software        2631\n",
            "Gadgets         2336\n",
            "Plays           1184\n",
            "Apps            1168\n",
            "Wearables        971\n",
            "Musical          791\n",
            "Sound            528\n",
            "Festivals        482\n",
            "Robots           473\n",
            "Flight           373\n",
            "Experimental     321\n",
            "Immersive        277\n",
            "Makerspaces      203\n",
            "Spaces           182\n",
            "Places           100\n",
            "Shorts            40\n",
            "Thrillers         20\n",
            "Webseries         20\n",
            "Restaurants       20\n",
            "Blues             20\n",
            "Academic          20\n",
            "Comedy            10\n",
            "Name: category, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('profile')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dBgmQvDfbHEb",
        "outputId": "ee923b15-64f7-4b5b-959a-ffa9385d1629"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    {\"background_image_opacity\":0.8,\"should_show_f...\n",
            "1    {\"background_image_opacity\":0.8,\"should_show_f...\n",
            "2    {\"background_image_opacity\":0.8,\"should_show_f...\n",
            "3    {\"background_image_opacity\":0.8,\"should_show_f...\n",
            "4    {\"background_image_opacity\":0.8,\"should_show_f...\n",
            "Name: profile, dtype: object\n",
            "\n",
            "\n",
            "{\"background_image_opacity\":0.8,\"should_show_feature_image_section\":true,\"link_text_color\":null,\"state_changed_at\":1425915885,\"blurb\":null,\"background_color\":null,\"project_id\":1546341,\"name\":null,\"feature_image_attributes\":{\"image_urls\":{\"default\":\"https://ksr-ugc.imgix.net/assets/011/959/953/4e53aa51f82e9764b135307761da1cde_original.JPG?w=1552&h=873&fit=fill&bg=000000&v=1463719439&auto=format&q=92&s=70c684eaeb2b96fff3283fa72daeabee\",\"baseball_card\":\"https://ksr-ugc.imgix.net/assets/011/959/953/4e53aa51f82e9764b135307761da1cde_original.JPG?w=1552&h=873&fit=fill&bg=000000&v=1463719439&auto=format&q=92&s=70c684eaeb2b96fff3283fa72daeabee\"}},\"link_url\":null,\"show_feature_image\":false,\"id\":1546341,\"state\":\"inactive\",\"text_color\":null,\"link_text\":null,\"link_background_color\":null}    1\n",
            "{\"background_image_opacity\":0.8,\"should_show_feature_image_section\":true,\"link_text_color\":null,\"state_changed_at\":1425915845,\"blurb\":null,\"background_color\":null,\"project_id\":831917,\"name\":null,\"feature_image_attributes\":{\"image_urls\":{\"default\":\"https://ksr-ugc.imgix.net/assets/011/629/055/7107e879438ff159da1e5562b4635d8d_original.jpg?w=1552&h=873&fit=fill&bg=000000&v=1463685804&auto=format&q=92&s=5c88d40ba9e6011b61e5430c9bf2efd3\",\"baseball_card\":\"https://ksr-ugc.imgix.net/assets/011/629/055/7107e879438ff159da1e5562b4635d8d_original.jpg?w=1552&h=873&fit=fill&bg=000000&v=1463685804&auto=format&q=92&s=5c88d40ba9e6011b61e5430c9bf2efd3\"}},\"link_url\":null,\"show_feature_image\":false,\"id\":831917,\"state\":\"inactive\",\"text_color\":null,\"link_text\":null,\"link_background_color\":null}      1\n",
            "{\"background_image_opacity\":0.8,\"should_show_feature_image_section\":true,\"link_text_color\":null,\"state_changed_at\":1425915826,\"blurb\":null,\"background_color\":null,\"project_id\":473902,\"name\":null,\"feature_image_attributes\":{\"image_urls\":{\"default\":\"https://ksr-ugc.imgix.net/assets/011/482/002/c747b5a3c8b7012468bf5583e9ce1392_original.jpg?w=1552&h=873&fit=fill&bg=000000&v=1463683338&auto=format&q=92&s=c937a53e370131864d74475b155d1823\",\"baseball_card\":\"https://ksr-ugc.imgix.net/assets/011/482/002/c747b5a3c8b7012468bf5583e9ce1392_original.jpg?w=1552&h=873&fit=fill&bg=000000&v=1463683338&auto=format&q=92&s=c937a53e370131864d74475b155d1823\"}},\"link_url\":null,\"show_feature_image\":false,\"id\":473902,\"state\":\"inactive\",\"text_color\":null,\"link_text\":null,\"link_background_color\":null}      1\n",
            "{\"background_image_opacity\":0.8,\"should_show_feature_image_section\":true,\"link_text_color\":null,\"state_changed_at\":1425915851,\"blurb\":null,\"background_color\":null,\"project_id\":937955,\"name\":null,\"feature_image_attributes\":{\"image_urls\":{\"default\":\"https://ksr-ugc.imgix.net/assets/011/670/341/aa99bf7686dd955e7de1108cee05c256_original.JPG?w=1552&h=873&fit=fill&bg=000000&v=1463686568&auto=format&q=92&s=d7786ed274a484432cb992fe62845afb\",\"baseball_card\":\"https://ksr-ugc.imgix.net/assets/011/670/341/aa99bf7686dd955e7de1108cee05c256_original.JPG?w=1552&h=873&fit=fill&bg=000000&v=1463686568&auto=format&q=92&s=d7786ed274a484432cb992fe62845afb\"}},\"link_url\":null,\"show_feature_image\":false,\"id\":937955,\"state\":\"inactive\",\"text_color\":null,\"link_text\":null,\"link_background_color\":null}      1\n",
            "{\"background_image_opacity\":0.8,\"should_show_feature_image_section\":true,\"link_text_color\":null,\"state_changed_at\":1425915825,\"blurb\":null,\"background_color\":null,\"project_id\":454070,\"name\":null,\"feature_image_attributes\":{\"image_urls\":{\"default\":\"https://ksr-ugc.imgix.net/assets/011/473/399/00b82dc62fae7f462ed7996bebde16ee_original.png?w=1552&h=873&fit=fill&bg=000000&v=1463683197&auto=format&q=92&s=d76fb5a8b731df3056d474b376d59a86\",\"baseball_card\":\"https://ksr-ugc.imgix.net/assets/011/473/399/00b82dc62fae7f462ed7996bebde16ee_original.png?w=1552&h=873&fit=fill&bg=000000&v=1463683197&auto=format&q=92&s=d76fb5a8b731df3056d474b376d59a86\"}},\"link_url\":null,\"show_feature_image\":false,\"id\":454070,\"state\":\"inactive\",\"text_color\":null,\"link_text\":null,\"link_background_color\":null}      1\n",
            "                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    ..\n",
            "{\"background_image_opacity\":0.8,\"should_show_feature_image_section\":true,\"link_text_color\":null,\"state_changed_at\":1425915870,\"blurb\":null,\"background_color\":null,\"project_id\":1269461,\"name\":null,\"feature_image_attributes\":{\"image_urls\":{\"default\":\"https://ksr-ugc.imgix.net/assets/011/826/429/2a165fcbf88e63d4766ad8268a6882e6_original.jpg?w=1552&h=873&fit=fill&bg=000000&v=1463700325&auto=format&q=92&s=a1a69f883a1024641c665851281a30ca\",\"baseball_card\":\"https://ksr-ugc.imgix.net/assets/011/826/429/2a165fcbf88e63d4766ad8268a6882e6_original.jpg?w=1552&h=873&fit=fill&bg=000000&v=1463700325&auto=format&q=92&s=a1a69f883a1024641c665851281a30ca\"}},\"link_url\":null,\"show_feature_image\":false,\"id\":1269461,\"state\":\"inactive\",\"text_color\":null,\"link_text\":null,\"link_background_color\":null}    1\n",
            "{\"background_image_opacity\":0.8,\"should_show_feature_image_section\":true,\"link_text_color\":null,\"state_changed_at\":1427895503,\"blurb\":null,\"background_color\":null,\"project_id\":1813915,\"name\":null,\"feature_image_attributes\":{\"image_urls\":{\"default\":\"https://ksr-ugc.imgix.net/assets/012/092/546/0abfc782cb750779417b153f553c7250_original.jpg?w=1552&h=873&fit=fill&bg=000000&v=1463731184&auto=format&q=92&s=70d15b31af19fd081ed37ccb3cd2f2b2\",\"baseball_card\":\"https://ksr-ugc.imgix.net/assets/012/092/546/0abfc782cb750779417b153f553c7250_original.jpg?w=1552&h=873&fit=fill&bg=000000&v=1463731184&auto=format&q=92&s=70d15b31af19fd081ed37ccb3cd2f2b2\"}},\"link_url\":null,\"show_feature_image\":false,\"id\":1813915,\"state\":\"inactive\",\"text_color\":null,\"link_text\":null,\"link_background_color\":null}    1\n",
            "{\"background_image_opacity\":0.8,\"should_show_feature_image_section\":true,\"link_text_color\":null,\"state_changed_at\":1425915893,\"blurb\":null,\"background_color\":null,\"project_id\":1700999,\"name\":null,\"feature_image_attributes\":{\"image_urls\":{\"default\":\"https://ksr-ugc.imgix.net/assets/012/034/753/303cc7499dfe12fdefc05b8541fa0828_original.jpg?w=1552&h=873&fit=fill&bg=000000&v=1463725927&auto=format&q=92&s=0bd94dd9e3d6079d0da3354760e43c84\",\"baseball_card\":\"https://ksr-ugc.imgix.net/assets/012/034/753/303cc7499dfe12fdefc05b8541fa0828_original.jpg?w=1552&h=873&fit=fill&bg=000000&v=1463725927&auto=format&q=92&s=0bd94dd9e3d6079d0da3354760e43c84\"}},\"link_url\":null,\"show_feature_image\":false,\"id\":1700999,\"state\":\"inactive\",\"text_color\":null,\"link_text\":null,\"link_background_color\":null}    1\n",
            "{\"background_image_opacity\":0.8,\"should_show_feature_image_section\":true,\"link_text_color\":null,\"state_changed_at\":1441098744,\"blurb\":null,\"background_color\":null,\"project_id\":2097254,\"name\":null,\"feature_image_attributes\":{\"image_urls\":{\"default\":\"https://ksr-ugc.imgix.net/assets/012/239/899/fe6eb25fd7c0a4c0200219a28a489f9c_original.png?w=1552&h=873&fit=fill&bg=000000&v=1463745397&auto=format&q=92&s=375dfb0c25266480947a9c0ba9556474\",\"baseball_card\":\"https://ksr-ugc.imgix.net/assets/012/239/899/fe6eb25fd7c0a4c0200219a28a489f9c_original.png?w=1552&h=873&fit=fill&bg=000000&v=1463745397&auto=format&q=92&s=375dfb0c25266480947a9c0ba9556474\"}},\"link_url\":null,\"show_feature_image\":false,\"id\":2097254,\"state\":\"inactive\",\"text_color\":null,\"link_text\":null,\"link_background_color\":null}    1\n",
            "{\"background_image_opacity\":0.8,\"should_show_feature_image_section\":true,\"link_text_color\":null,\"state_changed_at\":1425915877,\"blurb\":null,\"background_color\":null,\"project_id\":1392604,\"name\":null,\"feature_image_attributes\":{\"image_urls\":{\"default\":\"https://ksr-ugc.imgix.net/assets/011/885/281/fef07d98c58402ed069f57b77011a54f_original.png?w=1552&h=873&fit=fill&bg=000000&v=1463710217&auto=format&q=92&s=6a783c522e07b73a672ae579925a30e3\",\"baseball_card\":\"https://ksr-ugc.imgix.net/assets/011/885/281/fef07d98c58402ed069f57b77011a54f_original.png?w=1552&h=873&fit=fill&bg=000000&v=1463710217&auto=format&q=92&s=6a783c522e07b73a672ae579925a30e3\"}},\"link_url\":null,\"show_feature_image\":false,\"id\":1392604,\"state\":\"inactive\",\"text_color\":null,\"link_text\":null,\"link_background_color\":null}    1\n",
            "Name: profile, Length: 20632, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('spotlight')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LyLg2xgobM_E",
        "outputId": "65401dc3-9c41-4a5d-b2d3-8be73db7bff2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    False\n",
            "1    False\n",
            "2    False\n",
            "3    False\n",
            "4    False\n",
            "Name: spotlight, dtype: bool\n",
            "\n",
            "\n",
            "False    14614\n",
            "True      6018\n",
            "Name: spotlight, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('urls')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yG2MZfUsbQ-G",
        "outputId": "504587e1-01e8-4db2-b3ac-9f6258d6e2fc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    {\"web\":{\"project\":\"https://www.kickstarter.com...\n",
            "1    {\"web\":{\"project\":\"https://www.kickstarter.com...\n",
            "2    {\"web\":{\"project\":\"https://www.kickstarter.com...\n",
            "3    {\"web\":{\"project\":\"https://www.kickstarter.com...\n",
            "4    {\"web\":{\"project\":\"https://www.kickstarter.com...\n",
            "Name: urls, dtype: object\n",
            "\n",
            "\n",
            "{\"web\":{\"project\":\"https://www.kickstarter.com/projects/1469579873/auntie-dis-music-time-sign-asl-for-hearing-and-hoh?ref=category\",\"rewards\":\"https://www.kickstarter.com/projects/1469579873/auntie-dis-music-time-sign-asl-for-hearing-and-hoh/rewards\"}}    1\n",
            "{\"web\":{\"project\":\"https://www.kickstarter.com/projects/okaytotell/jackie-and-the-beanstalk-a-re-spun-yarn?ref=category\",\"rewards\":\"https://www.kickstarter.com/projects/okaytotell/jackie-and-the-beanstalk-a-re-spun-yarn/rewards\"}}                          1\n",
            "{\"web\":{\"project\":\"https://www.kickstarter.com/projects/piq/piq-a-jukebox-for-social-spaces?ref=category\",\"rewards\":\"https://www.kickstarter.com/projects/piq/piq-a-jukebox-for-social-spaces/rewards\"}}                                                        1\n",
            "{\"web\":{\"project\":\"https://www.kickstarter.com/projects/motool/presenting-slacker-a-revolutionary-new-tool?ref=category\",\"rewards\":\"https://www.kickstarter.com/projects/motool/presenting-slacker-a-revolutionary-new-tool/rewards\"}}                          1\n",
            "{\"web\":{\"project\":\"https://www.kickstarter.com/projects/1880021630/energybridge-solar-power-grid-tie-and-backup-in-on?ref=category\",\"rewards\":\"https://www.kickstarter.com/projects/1880021630/energybridge-solar-power-grid-tie-and-backup-in-on/rewards\"}}    1\n",
            "                                                                                                                                                                                                                                                               ..\n",
            "{\"web\":{\"project\":\"https://www.kickstarter.com/projects/391352938/breanna-jean?ref=category\",\"rewards\":\"https://www.kickstarter.com/projects/391352938/breanna-jean/rewards\"}}                                                                                  1\n",
            "{\"web\":{\"project\":\"https://www.kickstarter.com/projects/254998388/website-building-app?ref=category\",\"rewards\":\"https://www.kickstarter.com/projects/254998388/website-building-app/rewards\"}}                                                                  1\n",
            "{\"web\":{\"project\":\"https://www.kickstarter.com/projects/789366595/website-for-parents-of-twins-and-multiples?ref=category\",\"rewards\":\"https://www.kickstarter.com/projects/789366595/website-for-parents-of-twins-and-multiples/rewards\"}}                      1\n",
            "{\"web\":{\"project\":\"https://www.kickstarter.com/projects/2011577162/annuaire-des-artisans-marocains-sans-moyen-de-mark?ref=category\",\"rewards\":\"https://www.kickstarter.com/projects/2011577162/annuaire-des-artisans-marocains-sans-moyen-de-mark/rewards\"}}    1\n",
            "{\"web\":{\"project\":\"https://www.kickstarter.com/projects/1857230317/lets-trail-app?ref=category\",\"rewards\":\"https://www.kickstarter.com/projects/1857230317/lets-trail-app/rewards\"}}                                                                            1\n",
            "Name: urls, Length: 20632, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('source_url')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wcDQnaG9bXXR",
        "outputId": "364f4020-2233-4cb9-c5c3-029dfc4c7289"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    https://www.kickstarter.com/discover/categorie...\n",
            "1    https://www.kickstarter.com/discover/categorie...\n",
            "2    https://www.kickstarter.com/discover/categorie...\n",
            "3    https://www.kickstarter.com/discover/categorie...\n",
            "4    https://www.kickstarter.com/discover/categorie...\n",
            "Name: source_url, dtype: object\n",
            "\n",
            "\n",
            "https://www.kickstarter.com/discover/categories/technology/web?ref=category_modal&sort=magic                       3325\n",
            "https://www.kickstarter.com/discover/categories/technology/hardware?ref=category_modal&sort=magic                  3248\n",
            "https://www.kickstarter.com/discover/categories/technology/software?ref=category_modal&sort=magic                  2631\n",
            "https://www.kickstarter.com/discover/categories/technology/gadgets?ref=category_modal&sort=magic                   2336\n",
            "https://www.kickstarter.com/discover/categories/theater/plays?ref=category_modal&sort=magic                        1184\n",
            "https://www.kickstarter.com/discover/categories/technology/apps?ref=category_modal&sort=magic                      1168\n",
            "https://www.kickstarter.com/discover/categories/technology/wearables?ref=category_modal&sort=magic                  971\n",
            "https://www.kickstarter.com/discover/categories/theater/musical?ref=category_modal&sort=magic                       791\n",
            "https://www.kickstarter.com/discover/categories/technology/diy%20electronics?ref=category_modal&sort=magic          735\n",
            "https://www.kickstarter.com/discover/categories/technology/sound?ref=category_modal&sort=magic                      528\n",
            "https://www.kickstarter.com/discover/categories/theater/festivals?ref=category_modal&sort=magic                     482\n",
            "https://www.kickstarter.com/discover/categories/technology/robots?ref=category_modal&sort=magic                     473\n",
            "https://www.kickstarter.com/discover/categories/technology/flight?ref=category_modal&sort=magic                     373\n",
            "https://www.kickstarter.com/discover/categories/technology/camera%20equipment?ref=category_modal&sort=magic         337\n",
            "https://www.kickstarter.com/discover/categories/theater/experimental?ref=category_modal&sort=magic                  321\n",
            "https://www.kickstarter.com/discover/categories/theater/immersive?ref=category_modal&sort=magic                     277\n",
            "https://www.kickstarter.com/discover/categories/technology/space%20exploration?ref=category_modal&sort=magic        270\n",
            "https://www.kickstarter.com/discover/categories/technology/fabrication%20tools?ref=category_modal&sort=magic        207\n",
            "https://www.kickstarter.com/discover/categories/technology/makerspaces?ref=category_modal&sort=magic                203\n",
            "https://www.kickstarter.com/discover/categories/theater/spaces?ref=category_modal&sort=magic                        182\n",
            "https://www.kickstarter.com/discover/categories/games/video%20games?ref=category_modal&sort=magic                   140\n",
            "https://www.kickstarter.com/discover/categories/photography/places?ref=category_modal&sort=magic                    100\n",
            "https://www.kickstarter.com/discover/categories/music/electronic%20music?ref=category_modal&sort=magic               60\n",
            "https://www.kickstarter.com/discover/categories/music/country%20&%20folk?ref=category_modal&sort=magic               60\n",
            "https://www.kickstarter.com/discover/categories/music/classical%20music?ref=category_modal&sort=magic                40\n",
            "https://www.kickstarter.com/discover/categories/film%20&%20video/narrative%20film?ref=category_modal&sort=magic      40\n",
            "https://www.kickstarter.com/discover/categories/film%20&%20video/shorts?ref=category_modal&sort=magic                40\n",
            "https://www.kickstarter.com/discover/categories/music/blues?ref=category_modal&sort=magic                            20\n",
            "https://www.kickstarter.com/discover/categories/food/restaurants?ref=category_modal&sort=magic                       20\n",
            "https://www.kickstarter.com/discover/categories/film%20&%20video/webseries?ref=category_modal&sort=magic             20\n",
            "https://www.kickstarter.com/discover/categories/film%20&%20video/thrillers?ref=category_modal&sort=magic             20\n",
            "https://www.kickstarter.com/discover/categories/publishing/academic?ref=category_modal&sort=magic                    20\n",
            "https://www.kickstarter.com/discover/categories/theater/comedy?ref=category_modal&sort=magic                         10\n",
            "Name: source_url, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('name_len')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3e3XURuhbre8",
        "outputId": "6093610b-c207-48b5-e7fc-e2e7c5d176f0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    11.0\n",
            "1     4.0\n",
            "2     8.0\n",
            "3     7.0\n",
            "4     7.0\n",
            "Name: name_len, dtype: float64\n",
            "\n",
            "\n",
            "8.0     2610\n",
            "7.0     2531\n",
            "6.0     2298\n",
            "5.0     2074\n",
            "4.0     2030\n",
            "9.0     2022\n",
            "3.0     1962\n",
            "2.0     1568\n",
            "1.0     1346\n",
            "10.0    1291\n",
            "11.0     630\n",
            "12.0     209\n",
            "13.0      40\n",
            "14.0       9\n",
            "15.0       6\n",
            "16.0       1\n",
            "Name: name_len, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('name_len_clean')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0e9px-rYeadX",
        "outputId": "e002ca70-1b07-46e2-a4a8-4018709414d7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    9.0\n",
            "1    4.0\n",
            "2    8.0\n",
            "3    6.0\n",
            "4    7.0\n",
            "Name: name_len_clean, dtype: float64\n",
            "\n",
            "\n",
            "6.0     3128\n",
            "7.0     2941\n",
            "5.0     2727\n",
            "4.0     2449\n",
            "3.0     2264\n",
            "8.0     2123\n",
            "2.0     1781\n",
            "1.0     1356\n",
            "9.0     1164\n",
            "10.0     485\n",
            "11.0     157\n",
            "12.0      41\n",
            "13.0       9\n",
            "14.0       2\n",
            "Name: name_len_clean, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('blurb_len')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZSsEPt-wbvk5",
        "outputId": "6dc5f8ab-5c78-4aac-f151-ec9bb005c7be"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    21.0\n",
            "1    23.0\n",
            "2    18.0\n",
            "3    21.0\n",
            "4    18.0\n",
            "Name: blurb_len, dtype: float64\n",
            "\n",
            "\n",
            "20.0    2202\n",
            "21.0    2178\n",
            "22.0    2081\n",
            "19.0    1963\n",
            "23.0    1720\n",
            "18.0    1573\n",
            "17.0    1268\n",
            "24.0    1214\n",
            "16.0     949\n",
            "25.0     793\n",
            "15.0     769\n",
            "14.0     581\n",
            "13.0     506\n",
            "12.0     426\n",
            "26.0     425\n",
            "11.0     353\n",
            "9.0      278\n",
            "10.0     276\n",
            "8.0      210\n",
            "27.0     205\n",
            "7.0      168\n",
            "6.0      123\n",
            "5.0       88\n",
            "28.0      79\n",
            "4.0       54\n",
            "3.0       37\n",
            "1.0       37\n",
            "29.0      35\n",
            "2.0       18\n",
            "30.0      13\n",
            "31.0       4\n",
            "35.0       1\n",
            "Name: blurb_len, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('blurb_len_clean')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CYYcSXmGgsdb",
        "outputId": "c876e097-45a6-4bbc-861e-115d4e3ed8db"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    16.0\n",
            "1    15.0\n",
            "2    10.0\n",
            "3    13.0\n",
            "4    18.0\n",
            "Name: blurb_len_clean, dtype: float64\n",
            "\n",
            "\n",
            "14.0    3169\n",
            "13.0    2877\n",
            "15.0    2597\n",
            "12.0    2347\n",
            "16.0    1846\n",
            "11.0    1597\n",
            "17.0    1118\n",
            "10.0    1111\n",
            "9.0      756\n",
            "8.0      605\n",
            "18.0     598\n",
            "7.0      504\n",
            "6.0      326\n",
            "19.0     303\n",
            "5.0      237\n",
            "20.0     162\n",
            "4.0      124\n",
            "21.0      78\n",
            "22.0      64\n",
            "3.0       63\n",
            "1.0       38\n",
            "2.0       32\n",
            "23.0      32\n",
            "24.0      20\n",
            "25.0      15\n",
            "28.0       5\n",
            "26.0       1\n",
            "27.0       1\n",
            "30.0       1\n",
            "Name: blurb_len_clean, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('deadline_weekday')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rDpquUtqgxnY",
        "outputId": "3e9550de-ce31-4c66-e259-68ad74a24cf1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0      Friday\n",
            "1      Friday\n",
            "2    Thursday\n",
            "3      Monday\n",
            "4      Monday\n",
            "Name: deadline_weekday, dtype: object\n",
            "\n",
            "\n",
            "Friday       3764\n",
            "Thursday     3444\n",
            "Wednesday    3202\n",
            "Sunday       3041\n",
            "Saturday     2984\n",
            "Monday       2221\n",
            "Tuesday      1976\n",
            "Name: deadline_weekday, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('state_changed_at_weekday')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BsCmG1jbg9rm",
        "outputId": "4b9ffe04-cba0-4cc6-8798-1a9cf47f81a6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0      Friday\n",
            "1      Friday\n",
            "2    Thursday\n",
            "3      Monday\n",
            "4      Monday\n",
            "Name: state_changed_at_weekday, dtype: object\n",
            "\n",
            "\n",
            "Friday       3651\n",
            "Thursday     3439\n",
            "Wednesday    3264\n",
            "Sunday       2836\n",
            "Saturday     2806\n",
            "Monday       2398\n",
            "Tuesday      2238\n",
            "Name: state_changed_at_weekday, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('created_at_weekday')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IuPo6JHUhDJd",
        "outputId": "269e9408-1d86-4458-d5bc-d50220538081"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0     Saturday\n",
            "1       Friday\n",
            "2     Saturday\n",
            "3       Friday\n",
            "4    Wednesday\n",
            "Name: created_at_weekday, dtype: object\n",
            "\n",
            "\n",
            "Tuesday      3612\n",
            "Monday       3474\n",
            "Wednesday    3325\n",
            "Thursday     3155\n",
            "Friday       2699\n",
            "Sunday       2277\n",
            "Saturday     2090\n",
            "Name: created_at_weekday, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('launched_at_weekday')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-5ukx2SIhIb5",
        "outputId": "46195c15-6810-4fc8-e477-f1996f4d6876"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    Wednesday\n",
            "1       Monday\n",
            "2       Sunday\n",
            "3     Saturday\n",
            "4     Thursday\n",
            "Name: launched_at_weekday, dtype: object\n",
            "\n",
            "\n",
            "Tuesday      4645\n",
            "Monday       4200\n",
            "Wednesday    3741\n",
            "Thursday     3094\n",
            "Friday       2818\n",
            "Saturday     1075\n",
            "Sunday       1059\n",
            "Name: launched_at_weekday, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('deadline_month')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "znSIGxWxhP6I",
        "outputId": "2a54518a-8554-419a-d064-692e848f70fe"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0     1\n",
            "1     5\n",
            "2     3\n",
            "3    10\n",
            "4     6\n",
            "Name: deadline_month, dtype: int64\n",
            "\n",
            "\n",
            "12    1954\n",
            "8     1954\n",
            "7     1906\n",
            "3     1778\n",
            "9     1732\n",
            "10    1713\n",
            "11    1704\n",
            "5     1680\n",
            "6     1673\n",
            "4     1575\n",
            "1     1487\n",
            "2     1476\n",
            "Name: deadline_month, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('deadline_day')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AUGmbRYXhR1w",
        "outputId": "56403fb5-6bae-4609-e505-5b59c7db8e05"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    23\n",
            "1     1\n",
            "2    26\n",
            "3     6\n",
            "4    27\n",
            "Name: deadline_day, dtype: int64\n",
            "\n",
            "\n",
            "1     878\n",
            "15    800\n",
            "30    760\n",
            "10    712\n",
            "8     697\n",
            "2     685\n",
            "17    684\n",
            "20    683\n",
            "16    680\n",
            "12    675\n",
            "31    674\n",
            "3     674\n",
            "5     671\n",
            "4     662\n",
            "25    659\n",
            "7     656\n",
            "19    654\n",
            "11    652\n",
            "18    650\n",
            "13    644\n",
            "9     643\n",
            "6     641\n",
            "14    637\n",
            "21    632\n",
            "27    617\n",
            "26    616\n",
            "28    613\n",
            "29    612\n",
            "23    598\n",
            "24    592\n",
            "22    581\n",
            "Name: deadline_day, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('deadline_yr')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "th6Lm7F_hW5x",
        "outputId": "fafa7758-0a1b-408c-c361-71ea6bb528ce"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    2015\n",
            "1    2015\n",
            "2    2015\n",
            "3    2014\n",
            "4    2016\n",
            "Name: deadline_yr, dtype: int64\n",
            "\n",
            "\n",
            "2015    7366\n",
            "2016    5237\n",
            "2014    4819\n",
            "2013    1110\n",
            "2017    1081\n",
            "2012     519\n",
            "2011     279\n",
            "2010     185\n",
            "2009      36\n",
            "Name: deadline_yr, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('deadline_hr')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AO4iKgiGhgKY",
        "outputId": "99371e0d-bcac-4e7b-b1f2-3ce01fce7443"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    10\n",
            "1    16\n",
            "2     8\n",
            "3     0\n",
            "4    12\n",
            "Name: deadline_hr, dtype: int64\n",
            "\n",
            "\n",
            "11    1496\n",
            "10    1344\n",
            "14    1292\n",
            "16    1278\n",
            "12    1193\n",
            "17    1175\n",
            "13    1171\n",
            "15    1165\n",
            "22    1051\n",
            "9      980\n",
            "18     935\n",
            "19     859\n",
            "23     812\n",
            "8      756\n",
            "20     713\n",
            "21     682\n",
            "1      611\n",
            "7      584\n",
            "0      529\n",
            "6      515\n",
            "2      463\n",
            "5      390\n",
            "3      338\n",
            "4      300\n",
            "Name: deadline_hr, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('state_changed_at_month')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2fi-EAGZhpKi",
        "outputId": "0c7cab26-f5f3-4e5d-d19c-53d0da093d39"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0     1\n",
            "1     5\n",
            "2     3\n",
            "3    10\n",
            "4     6\n",
            "Name: state_changed_at_month, dtype: int64\n",
            "\n",
            "\n",
            "12    1944\n",
            "8     1935\n",
            "7     1919\n",
            "1     1743\n",
            "11    1729\n",
            "10    1726\n",
            "9     1712\n",
            "6     1710\n",
            "5     1666\n",
            "4     1546\n",
            "2     1523\n",
            "3     1479\n",
            "Name: state_changed_at_month, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('state_changed_at_day')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DLfzaapzhtCN",
        "outputId": "7ab8ecdd-4051-4e46-fd48-911109e3afac"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    23\n",
            "1     1\n",
            "2    26\n",
            "3     6\n",
            "4    27\n",
            "Name: state_changed_at_day, dtype: int64\n",
            "\n",
            "\n",
            "1     847\n",
            "15    771\n",
            "30    740\n",
            "12    705\n",
            "8     701\n",
            "20    694\n",
            "3     693\n",
            "6     686\n",
            "10    685\n",
            "18    677\n",
            "7     674\n",
            "2     670\n",
            "4     666\n",
            "17    663\n",
            "5     662\n",
            "13    661\n",
            "31    660\n",
            "11    659\n",
            "9     658\n",
            "19    656\n",
            "14    652\n",
            "16    648\n",
            "25    633\n",
            "28    625\n",
            "23    620\n",
            "21    618\n",
            "26    617\n",
            "27    614\n",
            "29    605\n",
            "24    600\n",
            "22    572\n",
            "Name: state_changed_at_day, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('state_changed_at_yr')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "imzHszHshzhn",
        "outputId": "c4c5bf07-422c-42e9-e725-5e79c7ee24d1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    2015\n",
            "1    2015\n",
            "2    2015\n",
            "3    2014\n",
            "4    2016\n",
            "Name: state_changed_at_yr, dtype: int64\n",
            "\n",
            "\n",
            "2015    7348\n",
            "2016    5253\n",
            "2014    4868\n",
            "2013    1117\n",
            "2017    1027\n",
            "2012     518\n",
            "2011     279\n",
            "2010     185\n",
            "2009      37\n",
            "Name: state_changed_at_yr, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('state_changed_at_hr')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "l3TATVgth2_L",
        "outputId": "fcd836f8-ea39-44f0-8b38-7ccecc2278f0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    10\n",
            "1    16\n",
            "2     8\n",
            "3     0\n",
            "4    12\n",
            "Name: state_changed_at_hr, dtype: int64\n",
            "\n",
            "\n",
            "11    1482\n",
            "10    1322\n",
            "14    1289\n",
            "16    1286\n",
            "12    1239\n",
            "13    1196\n",
            "15    1171\n",
            "17    1166\n",
            "22    1000\n",
            "9      982\n",
            "18     932\n",
            "19     841\n",
            "23     794\n",
            "8      764\n",
            "20     707\n",
            "21     669\n",
            "7      581\n",
            "1      574\n",
            "0      543\n",
            "6      512\n",
            "2      482\n",
            "5      422\n",
            "3      360\n",
            "4      318\n",
            "Name: state_changed_at_hr, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('created_at_month')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "drrUkjlNh6cQ",
        "outputId": "4b7af59b-32a8-4f2a-8257-32904574de92"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    11\n",
            "1     2\n",
            "2     1\n",
            "3     9\n",
            "4     5\n",
            "Name: created_at_month, dtype: int64\n",
            "\n",
            "\n",
            "7     2106\n",
            "10    1847\n",
            "5     1835\n",
            "6     1777\n",
            "8     1756\n",
            "4     1686\n",
            "11    1685\n",
            "1     1667\n",
            "9     1666\n",
            "3     1643\n",
            "2     1597\n",
            "12    1367\n",
            "Name: created_at_month, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('created_at_day')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EUGYfZ5siEhU",
        "outputId": "c2cecdd8-dc69-4a22-8395-51815fc2973e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    29\n",
            "1    20\n",
            "2    24\n",
            "3     5\n",
            "4    25\n",
            "Name: created_at_day, dtype: int64\n",
            "\n",
            "\n",
            "8     771\n",
            "5     742\n",
            "13    713\n",
            "17    706\n",
            "9     705\n",
            "1     705\n",
            "28    702\n",
            "27    699\n",
            "10    697\n",
            "7     696\n",
            "23    695\n",
            "22    689\n",
            "6     686\n",
            "3     680\n",
            "12    680\n",
            "18    678\n",
            "11    675\n",
            "15    672\n",
            "19    671\n",
            "26    666\n",
            "16    659\n",
            "14    658\n",
            "2     658\n",
            "25    656\n",
            "4     649\n",
            "21    634\n",
            "20    631\n",
            "29    624\n",
            "24    603\n",
            "30    589\n",
            "31    343\n",
            "Name: created_at_day, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('created_at_yr')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sPIK0kCIiIfQ",
        "outputId": "66f3e03e-e6f7-401d-ae6e-43c9024d65f9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    2014\n",
            "1    2015\n",
            "2    2015\n",
            "3    2014\n",
            "4    2016\n",
            "Name: created_at_yr, dtype: int64\n",
            "\n",
            "\n",
            "2015    6953\n",
            "2014    5732\n",
            "2016    4850\n",
            "2013    1434\n",
            "2012     733\n",
            "2017     358\n",
            "2011     309\n",
            "2010     209\n",
            "2009      54\n",
            "Name: created_at_yr, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('created_at_hr')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8ioEm2xbiN-r",
        "outputId": "6dbbab0c-44e0-411c-8247-d9e19e21cbc4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    22\n",
            "1     9\n",
            "2     0\n",
            "3    22\n",
            "4    14\n",
            "Name: created_at_hr, dtype: int64\n",
            "\n",
            "\n",
            "15    1331\n",
            "12    1301\n",
            "13    1286\n",
            "14    1248\n",
            "11    1193\n",
            "10    1190\n",
            "16    1129\n",
            "17    1104\n",
            "9     1090\n",
            "18     930\n",
            "8      885\n",
            "19     865\n",
            "20     863\n",
            "21     835\n",
            "22     739\n",
            "7      659\n",
            "23     595\n",
            "6      565\n",
            "0      530\n",
            "4      503\n",
            "5      480\n",
            "3      453\n",
            "1      438\n",
            "2      420\n",
            "Name: created_at_hr, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('launched_at_month')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "g64-f7GziR6Q",
        "outputId": "e6eee7dd-cfb1-40c3-bd43-11bfbc1e75d3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    12\n",
            "1     3\n",
            "2     1\n",
            "3     9\n",
            "4     5\n",
            "Name: launched_at_month, dtype: int64\n",
            "\n",
            "\n",
            "7     1996\n",
            "11    1895\n",
            "6     1871\n",
            "10    1788\n",
            "5     1754\n",
            "8     1737\n",
            "9     1704\n",
            "2     1668\n",
            "1     1657\n",
            "3     1571\n",
            "4     1569\n",
            "12    1422\n",
            "Name: launched_at_month, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('launched_at_day')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OF9MOWZCiX1U",
        "outputId": "3eca182d-f8c6-41aa-ee33-f97e8ed2c7cb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    17\n",
            "1     2\n",
            "2    25\n",
            "3     6\n",
            "4    26\n",
            "Name: launched_at_day, dtype: int64\n",
            "\n",
            "\n",
            "1     807\n",
            "8     765\n",
            "2     750\n",
            "9     749\n",
            "15    722\n",
            "16    713\n",
            "10    707\n",
            "3     703\n",
            "13    701\n",
            "14    694\n",
            "20    687\n",
            "18    687\n",
            "4     683\n",
            "12    679\n",
            "17    679\n",
            "5     674\n",
            "23    672\n",
            "28    670\n",
            "11    670\n",
            "7     653\n",
            "21    648\n",
            "22    638\n",
            "6     636\n",
            "19    636\n",
            "30    620\n",
            "26    618\n",
            "25    618\n",
            "29    607\n",
            "27    600\n",
            "24    590\n",
            "31    356\n",
            "Name: launched_at_day, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('launched_at_day')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6EhfHrvvib8S",
        "outputId": "9e30ac06-2b46-44d1-cfc9-063b30dcb371"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    17\n",
            "1     2\n",
            "2    25\n",
            "3     6\n",
            "4    26\n",
            "Name: launched_at_day, dtype: int64\n",
            "\n",
            "\n",
            "1     807\n",
            "8     765\n",
            "2     750\n",
            "9     749\n",
            "15    722\n",
            "16    713\n",
            "10    707\n",
            "3     703\n",
            "13    701\n",
            "14    694\n",
            "20    687\n",
            "18    687\n",
            "4     683\n",
            "12    679\n",
            "17    679\n",
            "5     674\n",
            "23    672\n",
            "28    670\n",
            "11    670\n",
            "7     653\n",
            "21    648\n",
            "22    638\n",
            "6     636\n",
            "19    636\n",
            "30    620\n",
            "26    618\n",
            "25    618\n",
            "29    607\n",
            "27    600\n",
            "24    590\n",
            "31    356\n",
            "Name: launched_at_day, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('launched_at_yr')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Y6s5AZqvip8s",
        "outputId": "635efbdb-2550-44c5-8d9d-92c0065d2386"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    2014\n",
            "1    2015\n",
            "2    2015\n",
            "3    2014\n",
            "4    2016\n",
            "Name: launched_at_yr, dtype: int64\n",
            "\n",
            "\n",
            "2015    7264\n",
            "2014    5228\n",
            "2016    5223\n",
            "2013    1191\n",
            "2017     660\n",
            "2012     523\n",
            "2011     286\n",
            "2010     207\n",
            "2009      50\n",
            "Name: launched_at_yr, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('launched_at_hr')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7S5N_zvjivcZ",
        "outputId": "8fab2b48-1e42-466e-e75d-18fa6eed4655"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    13\n",
            "1    16\n",
            "2     8\n",
            "3     0\n",
            "4     5\n",
            "Name: launched_at_hr, dtype: int64\n",
            "\n",
            "\n",
            "11    1616\n",
            "10    1583\n",
            "14    1388\n",
            "12    1350\n",
            "13    1296\n",
            "15    1276\n",
            "16    1251\n",
            "9     1162\n",
            "17    1138\n",
            "8      912\n",
            "18     878\n",
            "19     750\n",
            "7      716\n",
            "20     681\n",
            "21     573\n",
            "23     566\n",
            "6      547\n",
            "22     491\n",
            "2      470\n",
            "0      439\n",
            "5      432\n",
            "3      391\n",
            "1      383\n",
            "4      343\n",
            "Name: launched_at_hr, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('create_to_launch')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JrqTRFhZix5Q",
        "outputId": "3b273191-19d9-4a89-d5bc-8bf28fb71658"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    17 days 14:51:39.000000000\n",
            "1    10 days 06:44:39.000000000\n",
            "2     1 days 08:08:58.000000000\n",
            "3     0 days 02:11:17.000000000\n",
            "4     0 days 15:47:38.000000000\n",
            "Name: create_to_launch, dtype: object\n",
            "\n",
            "\n",
            "7 days 22:59:25.000000000     2\n",
            "0 days 01:09:56.000000000     2\n",
            "0 days 02:47:05.000000000     2\n",
            "0 days 03:39:18.000000000     2\n",
            "1 days 21:00:38.000000000     2\n",
            "                             ..\n",
            "0 days 13:49:37.000000000     1\n",
            "96 days 16:47:58.000000000    1\n",
            "0 days 17:34:55.000000000     1\n",
            "41 days 13:41:27.000000000    1\n",
            "22 days 22:42:01.000000000    1\n",
            "Name: create_to_launch, Length: 20553, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('launch_to_deadline')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gOIxRX1vi2lA",
        "outputId": "1de39a6f-437b-4ddd-fb54-a21bb96bc1b3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    36 days 20:47:24.000000000\n",
            "1    60 days 00:00:00.000000000\n",
            "2    60 days 00:00:00.000000000\n",
            "3    30 days 00:00:00.000000000\n",
            "4    32 days 06:02:33.000000000\n",
            "Name: launch_to_deadline, dtype: object\n",
            "\n",
            "\n",
            "30 days 00:00:00.000000000    9110\n",
            "60 days 00:00:00.000000000    2041\n",
            "45 days 00:00:00.000000000    1129\n",
            "40 days 00:00:00.000000000     543\n",
            "35 days 00:00:00.000000000     487\n",
            "                              ... \n",
            "7 days 00:47:43.000000000        1\n",
            "19 days 00:22:14.000000000       1\n",
            "22 days 05:16:01.000000000       1\n",
            "21 days 22:34:17.000000000       1\n",
            "31 days 23:47:41.000000000       1\n",
            "Name: launch_to_deadline, Length: 4987, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('launch_to_state_change')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oog3MufBi5FM",
        "outputId": "2488b2da-1fe8-4a10-e9a8-ff9dd3aaf1d7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    36 days 20:47:24.000000000\n",
            "1    60 days 00:00:02.000000000\n",
            "2    60 days 00:00:01.000000000\n",
            "3    30 days 00:00:00.000000000\n",
            "4    32 days 06:02:33.000000000\n",
            "Name: launch_to_state_change, dtype: object\n",
            "\n",
            "\n",
            "30 days 00:00:00.000000000    4167\n",
            "30 days 00:00:01.000000000    1501\n",
            "60 days 00:00:00.000000000     860\n",
            "30 days 00:00:02.000000000     804\n",
            "30 days 00:00:03.000000000     472\n",
            "                              ... \n",
            "24 days 05:30:53.000000000       1\n",
            "35 days 10:28:10.000000000       1\n",
            "30 days 09:48:28.000000000       1\n",
            "46 days 00:31:36.000000000       1\n",
            "31 days 23:47:42.000000000       1\n",
            "Name: launch_to_state_change, Length: 7544, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('create_to_launch_days')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ft6qAQMpi7qf",
        "outputId": "630063b6-eaa1-4845-e683-ab67fca7eacf"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    17\n",
            "1    10\n",
            "2     1\n",
            "3     0\n",
            "4     0\n",
            "Name: create_to_launch_days, dtype: int64\n",
            "\n",
            "\n",
            "0      1905\n",
            "1      1324\n",
            "2      1071\n",
            "3       919\n",
            "4       790\n",
            "       ... \n",
            "378       1\n",
            "540       1\n",
            "434       1\n",
            "519       1\n",
            "561       1\n",
            "Name: create_to_launch_days, Length: 686, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "full_1['create_to_launch_days'].hist()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 453
        },
        "id": "g9DHRP6yktmN",
        "outputId": "8244f991-d6f2-43cc-ec1a-d8499d58309d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 227
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "full_1.boxplot(['create_to_launch_days'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 452
        },
        "id": "vEE23oKzk3cA",
        "outputId": "999c7419-a935-4364-8d23-7bdf31998fdb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 228
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('launch_to_deadline_days')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uXAaaJ0-i_eZ",
        "outputId": "8bfa0efb-584c-4bb1-8666-ac38cbfba079"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    36\n",
            "1    60\n",
            "2    60\n",
            "3    30\n",
            "4    32\n",
            "Name: launch_to_deadline_days, dtype: int64\n",
            "\n",
            "\n",
            "30    9492\n",
            "60    2048\n",
            "45    1223\n",
            "35     638\n",
            "40     632\n",
            "      ... \n",
            "75       1\n",
            "74       1\n",
            "84       1\n",
            "85       1\n",
            "77       1\n",
            "Name: launch_to_deadline_days, Length: 85, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "full_1['launch_to_deadline_days'].hist()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 451
        },
        "id": "W0du8G1YlCRs",
        "outputId": "a783e76a-6f90-4ac1-ba5b-c4fc8088f48f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 229
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "full_1.boxplot(['launch_to_deadline_days'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 452
        },
        "id": "na26AuWhlFSE",
        "outputId": "0108e1bd-b4df-4ee9-b74c-6edc1fd1c56a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 230
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('launch_to_state_change_days')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0Vu3r63EkVOX",
        "outputId": "d959e555-08b7-4317-f776-90e69d68d46b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    36\n",
            "1    60\n",
            "2    60\n",
            "3    30\n",
            "4    32\n",
            "Name: launch_to_state_change_days, dtype: int64\n",
            "\n",
            "\n",
            "30    8160\n",
            "60    1642\n",
            "45     988\n",
            "0      718\n",
            "35     547\n",
            "      ... \n",
            "70       2\n",
            "79       1\n",
            "74       1\n",
            "69       1\n",
            "84       1\n",
            "Name: launch_to_state_change_days, Length: 84, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "full_1['launch_to_state_change_days'].hist()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 451
        },
        "id": "I8__u3wnlMs_",
        "outputId": "81ae4804-4be2-483e-a221-afc9c23bc4a5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 231
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "full_1.boxplot('launch_to_state_change_days')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 452
        },
        "id": "BvxJEs2vlS5l",
        "outputId": "068cd4a2-e511-4312-9ab6-c1569a368660"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 232
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('SuccessfulBool')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uc6f5bDLlXX_",
        "outputId": "b74a5624-c429-4535-d9de-73ebc6afa6ac"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    0\n",
            "1    0\n",
            "2    0\n",
            "3    0\n",
            "4    0\n",
            "Name: SuccessfulBool, dtype: int64\n",
            "\n",
            "\n",
            "0    14614\n",
            "1     6018\n",
            "Name: SuccessfulBool, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('USorGB')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "--fUGL68ldCp",
        "outputId": "51df2d35-2577-4088-bea2-c2e6b3716703"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    1\n",
            "1    1\n",
            "2    1\n",
            "3    1\n",
            "4    0\n",
            "Name: USorGB, dtype: int64\n",
            "\n",
            "\n",
            "1    16639\n",
            "0     3993\n",
            "Name: USorGB, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('TOPCOUNTRY')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IV21mwPgljEd",
        "outputId": "bc22a679-bbbd-4d84-ddd1-ce1e1fa9362d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    1\n",
            "1    1\n",
            "2    1\n",
            "3    1\n",
            "4    0\n",
            "Name: TOPCOUNTRY, dtype: int64\n",
            "\n",
            "\n",
            "1    16840\n",
            "0     3792\n",
            "Name: TOPCOUNTRY, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('LaunchedTuesday')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "86ApoEHRlmMC",
        "outputId": "a670fc1a-222f-4397-cb0d-404de5017d80"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    0\n",
            "1    0\n",
            "2    0\n",
            "3    0\n",
            "4    0\n",
            "Name: LaunchedTuesday, dtype: int64\n",
            "\n",
            "\n",
            "0    15987\n",
            "1     4645\n",
            "Name: LaunchedTuesday, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature_eda('DeadlineWeekend')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LTXmP01KlpVy",
        "outputId": "c079618e-36af-412a-942f-7a2ae6aad4a0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    0\n",
            "1    0\n",
            "2    0\n",
            "3    0\n",
            "4    0\n",
            "Name: DeadlineWeekend, dtype: int64\n",
            "\n",
            "\n",
            "0    14607\n",
            "1     6025\n",
            "Name: DeadlineWeekend, dtype: int64\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#////// TQDM CODE https:/ import SnowballStemmer\n",
        "# stemmer = SnowballStemmer(\"english\")\n",
        "# full_1['name_stemmed'] = full_1.name.map(lambda x: ' '.join([stemmer.stem(y) for y in x.split(' ')]))\n",
        "# full_1['name_stemmed'].head()\n",
        "\n",
        "# from sklearn.feature_extraction.text import CountVectorizer\n",
        "# from sklearn.feature_extraction.text import TfidfTransformer\n",
        "\n",
        "# cvec = CountVectorizer(stop_words='english', min_df=7, max_df=0.1, ngram_range=(1,3))\n",
        "# cvec\n",
        "\n",
        "# from itertools import islice\n",
        "# cvec.fit(full_1.name_stemmed)\n",
        "# list(islice(cvec.vocabulary_.items(), 50))\n",
        "\n",
        "# len(cvec.vocabulary_)\n",
        "\n",
        "# cvec_counts = cvec.transform(full_1['name_stemmed'])\n",
        "\n",
        "# print('sparse matrix shape:', cvec_counts.shape)\n",
        "# print('nonzero count:', cvec_counts.nnz)\n",
        "# print('sparsity: %.2f%%' % (100.0 * cvec_counts.nnz / (cvec_counts.shape[0] * cvec_counts.shape[1])))\n",
        "\n",
        "# occ = np.asarray(cvec_counts.sum(axis=0)).ravel().tolist()\n",
        "# counts_df = pd.DataFrame({'term': cvec.get_feature_names_out(), 'occurrences': occ})\n",
        "# counts_df.sort_values(by='occurrences', ascending=True).head(20)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4fImHGjbY5Wo",
        "outputId": "4623a193-c389-4e3a-ac1d-d7aa7e92e569"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    aunti di music time sign asl for hear and hoh ...\n",
              "1                      jump start kindergarten toolkit\n",
              "2    ojukwu balewa awolowo (o.b.a.) public librari ...\n",
              "3         mastiz - [mas-tahyz, mas-tahyz]  - to spread\n",
              "4    synops der eu-dsgvo - artikel, erwägungsgründe...\n",
              "Name: name_stemmed, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.feature_extraction.text import CountVectorizer\n",
        "from sklearn.feature_extraction.text import TfidfTransformer\n",
        "\n",
        "cvec = CountVectorizer(stop_words='english', min_df=7, max_df=0.1, ngram_range=(1,3))\n",
        "cvec"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 75
        },
        "id": "hl9HIbogbY01",
        "outputId": "64674d56-d946-4f52-8d15-f9901aeb77b6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "CountVectorizer(max_df=0.1, min_df=7, ngram_range=(1, 3), stop_words='english')"
            ],
            "text/html": [
              "<style>#sk-container-id-18 {color: black;background-color: white;}#sk-container-id-18 pre{padding: 0;}#sk-container-id-18 div.sk-toggleable {background-color: white;}#sk-container-id-18 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-18 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-18 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-18 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-18 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-18 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-18 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-18 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-18 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-18 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-18 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-18 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-18 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-18 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-18 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-18 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-18 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-18 div.sk-item {position: relative;z-index: 1;}#sk-container-id-18 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-18 div.sk-item::before, #sk-container-id-18 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-18 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-18 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-18 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-18 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-18 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-18 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-18 div.sk-label-container {text-align: center;}#sk-container-id-18 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-18 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-18\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>CountVectorizer(max_df=0.1, min_df=7, ngram_range=(1, 3), stop_words=&#x27;english&#x27;)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-18\" type=\"checkbox\" checked><label for=\"sk-estimator-id-18\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">CountVectorizer</label><div class=\"sk-toggleable__content\"><pre>CountVectorizer(max_df=0.1, min_df=7, ngram_range=(1, 3), stop_words=&#x27;english&#x27;)</pre></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 85
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from itertools import islice\n",
        "cvec.fit(full_1.name_stemmed)\n",
        "list(islice(cvec.vocabulary_.items(), 50))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2ZgcOw_Obi-S",
        "outputId": "d257cfd7-4bf5-4a1a-a0fc-6154e3272d3e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[('di', 577),\n",
              " ('music', 1375),\n",
              " ('time', 2096),\n",
              " ('sign', 1854),\n",
              " ('hear', 977),\n",
              " ('children', 388),\n",
              " ('jump', 1137),\n",
              " ('start', 1966),\n",
              " ('toolkit', 2111),\n",
              " ('public', 1622),\n",
              " ('librari', 1203),\n",
              " ('spread', 1954),\n",
              " ('der', 557),\n",
              " ('shadow', 1830),\n",
              " ('school', 1783),\n",
              " ('board', 257),\n",
              " ('texa', 2068),\n",
              " ('research', 1709),\n",
              " ('aid', 68),\n",
              " ('invest', 1096),\n",
              " ('club', 417),\n",
              " ('collect', 432),\n",
              " ('work', 2303),\n",
              " ('build', 302),\n",
              " ('project', 1609),\n",
              " ('book', 263),\n",
              " ('explor', 739),\n",
              " ('futur', 869),\n",
              " ('want', 2237),\n",
              " ('learn', 1182),\n",
              " ('english', 700),\n",
              " ('mobil', 1334),\n",
              " ('class', 402),\n",
              " ('world', 2306),\n",
              " ('seek', 1809),\n",
              " ('sit', 1865),\n",
              " ('advanc', 58),\n",
              " ('document', 605),\n",
              " ('measur', 1295),\n",
              " ('diari', 578),\n",
              " ('read', 1663),\n",
              " ('vision', 2220),\n",
              " ('letter', 1200),\n",
              " ('john', 1129),\n",
              " ('send', 1814),\n",
              " ('play', 1543),\n",
              " ('course', 498),\n",
              " ('journey', 1132),\n",
              " ('south', 1933),\n",
              " ('photo', 1514)]"
            ]
          },
          "metadata": {},
          "execution_count": 86
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(cvec.vocabulary_)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JwMXoWYIbozk",
        "outputId": "c6b4b423-ea27-4430-f41d-9936aa071977"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2336"
            ]
          },
          "metadata": {},
          "execution_count": 87
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cvec_counts = cvec.transform(full_1['name_stemmed'])"
      ],
      "metadata": {
        "id": "L6-YjQcXfIIf"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print('sparse matrix shape:', cvec_counts.shape)\n",
        "print('nonzero count:', cvec_counts.nnz)\n",
        "print('sparsity: %.2f%%' % (100.0 * cvec_counts.nnz / (cvec_counts.shape[0] * cvec_counts.shape[1])))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xrydlWFWfP4a",
        "outputId": "616ac344-707a-4d42-a774-dc1989425c20"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "sparse matrix shape: (20632, 2336)\n",
            "nonzero count: 67505\n",
            "sparsity: 0.14%\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "occ = np.asarray(cvec_counts.sum(axis=0)).ravel().tolist()\n",
        "counts_df = pd.DataFrame({'term': cvec.get_feature_names_out(), 'occurrences': occ})\n",
        "counts_df.sort_values(by='occurrences', ascending=True).head(20)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 677
        },
        "id": "kSWqJ17zf2GE",
        "outputId": "9b1587f6-1495-4232-8303-3a94fe420c7d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                 term  occurrences\n",
              "851            french            7\n",
              "338             canva            7\n",
              "337           cannabi            7\n",
              "331     camera stabil            7\n",
              "811              flip            7\n",
              "815            flower            7\n",
              "816               fly            7\n",
              "818              foam            7\n",
              "321             caddi            7\n",
              "320               cad            7\n",
              "1437      onlin cours            7\n",
              "826         footprint            7\n",
              "1436  onlin communiti            7\n",
              "836           forward            7\n",
              "844               frc            7\n",
              "303       build robot            7\n",
              "846             freak            7\n",
              "848       free energi            7\n",
              "1681          recruit            7\n",
              "297             bubbl            7"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-c3c28822-951b-4bf3-bed2-e60ccf8e9349\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>term</th>\n",
              "      <th>occurrences</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>851</th>\n",
              "      <td>french</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>338</th>\n",
              "      <td>canva</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>337</th>\n",
              "      <td>cannabi</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>331</th>\n",
              "      <td>camera stabil</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>811</th>\n",
              "      <td>flip</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>815</th>\n",
              "      <td>flower</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>816</th>\n",
              "      <td>fly</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>818</th>\n",
              "      <td>foam</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>321</th>\n",
              "      <td>caddi</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>320</th>\n",
              "      <td>cad</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1437</th>\n",
              "      <td>onlin cours</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>826</th>\n",
              "      <td>footprint</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1436</th>\n",
              "      <td>onlin communiti</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>836</th>\n",
              "      <td>forward</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>844</th>\n",
              "      <td>frc</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>303</th>\n",
              "      <td>build robot</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>846</th>\n",
              "      <td>freak</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>848</th>\n",
              "      <td>free energi</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1681</th>\n",
              "      <td>recruit</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>297</th>\n",
              "      <td>bubbl</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c3c28822-951b-4bf3-bed2-e60ccf8e9349')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-c3c28822-951b-4bf3-bed2-e60ccf8e9349 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-c3c28822-951b-4bf3-bed2-e60ccf8e9349');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 96
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "full_1['backers_count'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Bb_tafzcGs5H",
        "outputId": "99a4af22-4afe-4bf5-b1d4-a822e8e80f2e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0       2936\n",
              "1       1914\n",
              "2       1276\n",
              "3        910\n",
              "4        714\n",
              "        ... \n",
              "1513       1\n",
              "3863       1\n",
              "2051       1\n",
              "737        1\n",
              "819        1\n",
              "Name: backers_count, Length: 1505, dtype: int64"
            ]
          },
          "metadata": {},
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              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "full['category'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QStWe7FAoYX_",
        "outputId": "e726186b-0e1c-4fb4-8c24-17631855f8e4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Web             3325\n",
              "Hardware        3248\n",
              "Software        2631\n",
              "Gadgets         2336\n",
              "Plays           1184\n",
              "Apps            1168\n",
              "Wearables        971\n",
              "Musical          791\n",
              "Sound            528\n",
              "Festivals        482\n",
              "Robots           473\n",
              "Flight           373\n",
              "Experimental     321\n",
              "Immersive        277\n",
              "Makerspaces      203\n",
              "Spaces           182\n",
              "Places           100\n",
              "Shorts            40\n",
              "Thrillers         20\n",
              "Webseries         20\n",
              "Restaurants       20\n",
              "Blues             20\n",
              "Academic          20\n",
              "Comedy            10\n",
              "Name: category, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
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    {
      "cell_type": "code",
      "source": [
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      "metadata": {
        "colab": {
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        },
        "id": "qd7f-8BSkcAA",
        "outputId": "4fade14b-d851-40c0-a244-d98a2c40979d"
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      "execution_count": null,
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        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Unnamed: 0', 'id', 'photo', 'name', 'blurb', 'goal', 'pledged',\n",
              "       'state', 'slug', 'disable_communication', 'country', 'currency',\n",
              "       'currency_symbol', 'currency_trailing_code', 'deadline',\n",
              "       'state_changed_at', 'created_at', 'launched_at', 'staff_pick',\n",
              "       'backers_count', 'static_usd_rate', 'usd_pledged', 'creator',\n",
              "       'location', 'category', 'profile', 'spotlight', 'urls', 'source_url',\n",
              "       'friends', 'is_starred', 'is_backing', 'permissions', 'name_len',\n",
              "       'name_len_clean', 'blurb_len', 'blurb_len_clean', 'deadline_weekday',\n",
              "       'state_changed_at_weekday', 'created_at_weekday', 'launched_at_weekday',\n",
              "       'deadline_month', 'deadline_day', 'deadline_yr', 'deadline_hr',\n",
              "       'state_changed_at_month', 'state_changed_at_day', 'state_changed_at_yr',\n",
              "       'state_changed_at_hr', 'created_at_month', 'created_at_day',\n",
              "       'created_at_yr', 'created_at_hr', 'launched_at_month',\n",
              "       'launched_at_day', 'launched_at_yr', 'launched_at_hr',\n",
              "       'create_to_launch', 'launch_to_deadline', 'launch_to_state_change',\n",
              "       'create_to_launch_days', 'launch_to_deadline_days',\n",
              "       'launch_to_state_change_days', 'SuccessfulBool', 'USorGB', 'TOPCOUNTRY',\n",
              "       'LaunchedTuesday', 'DeadlineWeekend'],\n",
              "      dtype='object')"
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          "execution_count": 11
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        "id": "8QRbpdTUpr_g",
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              "Index(['Unnamed: 0', 'id', 'photo', 'name', 'blurb', 'goal', 'pledged',\n",
              "       'state', 'slug', 'disable_communication', 'country', 'currency',\n",
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              "       'created_at_yr', 'created_at_hr', 'launched_at_month',\n",
              "       'launched_at_day', 'launched_at_yr', 'launched_at_hr',\n",
              "       'create_to_launch', 'launch_to_deadline', 'launch_to_state_change'],\n",
              "      dtype='object')"
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      "metadata": {
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        "id": "sk90ry2Bpzp5",
        "outputId": "89aeb4f6-71ea-4ba7-e231-8101156f2461"
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(20632, 68)"
            ]
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          "metadata": {},
          "execution_count": 14
        }
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        "outputId": "eebf226f-66dd-4404-c2bc-f08dc752e47f"
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      "outputs": [
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            "text/plain": [
              "(20632, 60)"
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          "execution_count": 15
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    {
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      "source": [
        "temp = full.iloc[:,:59]\n",
        "temp.columns"
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      "metadata": {
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              "Index(['Unnamed: 0', 'id', 'photo', 'name', 'blurb', 'goal', 'pledged',\n",
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              "       'launched_at_day', 'launched_at_yr', 'launched_at_hr',\n",
              "       'create_to_launch', 'launch_to_deadline'],\n",
              "      dtype='object')"
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          },
          "metadata": {},
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    {
      "cell_type": "code",
      "source": [
        "temp.equals(with_feature.iloc[:,:59])"
      ],
      "metadata": {
        "colab": {
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        "id": "irFObriEsntA",
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          "data": {
            "text/plain": [
              "True"
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          "metadata": {},
          "execution_count": 37
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              "      <td>NaN</td>\n",
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              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install ydata-profiling\n",
        "\n",
        "import ydata_profiling\n",
        "ydata_profiling.ProfileReport(temp)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 113,
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            "32f65ef1f1d146809f90b7f7e0f69349"
          ]
        },
        "id": "ub3hNnbzl4OL",
        "outputId": "ba551d7b-87ea-49fa-a5fd-5f0f6255c865"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Summarize dataset:   0%|          | 0/5 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "bbfa4c01699b460095dcf825638b256d"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Generate report structure:   0%|          | 0/1 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "b20da537824546efa6c256510a1b333c"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Render HTML:   0%|          | 0/1 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "a3288d2004e4434f910276eb565029d6"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Conclusion is that the full dataset already have dataset with features."
      ],
      "metadata": {
        "id": "BNQINYX4OPIk"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Using the Full DataSet"
      ],
      "metadata": {
        "id": "lW1jYq_0OZ0_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "full.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 664
        },
        "id": "XgHoIb2sOXpg",
        "outputId": "d17304f0-dc03-4047-fb77-fe3fe98985dc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "   Unnamed: 0          id                                              photo  \\\n",
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              "\n",
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              "   disable_communication  ...          launch_to_deadline  \\\n",
              "0                  False  ...  36 days 20:47:24.000000000   \n",
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              "\n",
              "       launch_to_state_change create_to_launch_days  launch_to_deadline_days  \\\n",
              "0  36 days 20:47:24.000000000                    17                       36   \n",
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              "\n",
              "  launch_to_state_change_days SuccessfulBool USorGB TOPCOUNTRY  \\\n",
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            ]
          },
          "metadata": {},
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "full.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FGPxuBcdOxWP",
        "outputId": "762ea164-9542-4d0e-dd3c-b0b5b0ac7c98"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(20632, 68)"
            ]
          },
          "metadata": {},
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(full.iloc[:,:36].isna().sum())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XZCYyME9OgMR",
        "outputId": "83ba8eed-a497-4f13-c5d3-8f752ce348be"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Unnamed: 0                    0\n",
            "id                            0\n",
            "photo                         0\n",
            "name                          0\n",
            "blurb                         5\n",
            "goal                          0\n",
            "pledged                       0\n",
            "state                         0\n",
            "slug                          0\n",
            "disable_communication         0\n",
            "country                       0\n",
            "currency                      0\n",
            "currency_symbol               0\n",
            "currency_trailing_code        0\n",
            "deadline                      0\n",
            "state_changed_at              0\n",
            "created_at                    0\n",
            "launched_at                   0\n",
            "staff_pick                    0\n",
            "backers_count                 0\n",
            "static_usd_rate               0\n",
            "usd_pledged                   0\n",
            "creator                       0\n",
            "location                     45\n",
            "category                   1889\n",
            "profile                       0\n",
            "spotlight                     0\n",
            "urls                          0\n",
            "source_url                    0\n",
            "friends                   20572\n",
            "is_starred                20572\n",
            "is_backing                20572\n",
            "permissions               20572\n",
            "name_len                      5\n",
            "name_len_clean                5\n",
            "blurb_len                     5\n",
            "dtype: int64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "full['state'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "smjSRc2PqGF0",
        "outputId": "e76d2746-a7bb-412c-9437-eac35000b0d9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "failed        11416\n",
              "successful     6018\n",
              "canceled       2460\n",
              "live            508\n",
              "suspended       230\n",
              "Name: state, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 68
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(full.iloc[:,36:].isna().sum())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ri_J3i_AOrPn",
        "outputId": "f9c27d80-9542-4674-9c64-73a5f119d81c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "blurb_len_clean                5\n",
            "deadline_weekday               0\n",
            "state_changed_at_weekday       0\n",
            "created_at_weekday             0\n",
            "launched_at_weekday            0\n",
            "deadline_month                 0\n",
            "deadline_day                   0\n",
            "deadline_yr                    0\n",
            "deadline_hr                    0\n",
            "state_changed_at_month         0\n",
            "state_changed_at_day           0\n",
            "state_changed_at_yr            0\n",
            "state_changed_at_hr            0\n",
            "created_at_month               0\n",
            "created_at_day                 0\n",
            "created_at_yr                  0\n",
            "created_at_hr                  0\n",
            "launched_at_month              0\n",
            "launched_at_day                0\n",
            "launched_at_yr                 0\n",
            "launched_at_hr                 0\n",
            "create_to_launch               0\n",
            "launch_to_deadline             0\n",
            "launch_to_state_change         0\n",
            "create_to_launch_days          0\n",
            "launch_to_deadline_days        0\n",
            "launch_to_state_change_days    0\n",
            "SuccessfulBool                 0\n",
            "USorGB                         0\n",
            "TOPCOUNTRY                     0\n",
            "LaunchedTuesday                0\n",
            "DeadlineWeekend                0\n",
            "dtype: int64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "removing features Unnamed: 0,id,photo,friends,is_starred, is_backing,permissions from the dataset              "
      ],
      "metadata": {
        "id": "sliC6SsMO4oV"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "full_1 = full.drop(['Unnamed: 0', 'id', 'photo', 'friends', 'is_starred', 'is_backing', 'permissions'], axis=1)"
      ],
      "metadata": {
        "id": "HD9g8MgCPP1x"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "full_1.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5zQrTskzPtBz",
        "outputId": "1b02eb62-19b8-4d7f-e51d-361301f06c9e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(20632, 61)"
            ]
          },
          "metadata": {},
          "execution_count": 57
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "full_1.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 647
        },
        "id": "2c5lHdZBQBn4",
        "outputId": "feecaa37-b06f-4c00-a688-73ffc1165980"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "                                                name  \\\n",
              "0  Auntie Di's Music Time Sign ASL for Hearing an...   \n",
              "1                    Jump Start Kindergarten Toolkit   \n",
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              "3      MASTIZE - [mas-TAHYZ, MAS-tahyz]  - to spread   \n",
              "4  Synopse der EU-DSGVO - Artikel, Erwägungsgründ...   \n",
              "\n",
              "                                               blurb      goal  pledged  \\\n",
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              "4  Zu den Artikeln der DSGVO sind die korrespondi...    3222.0    356.0   \n",
              "\n",
              "    state                                               slug  \\\n",
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              "4  failed  synopse-der-eu-dsgvo-artikel-erwagungsgrunde-bdsg   \n",
              "\n",
              "   disable_communication country currency currency_symbol  ...  \\\n",
              "0                  False      US      USD               $  ...   \n",
              "1                  False      US      USD               $  ...   \n",
              "2                  False      US      USD               $  ...   \n",
              "3                  False      US      USD               $  ...   \n",
              "4                  False      DE      EUR               €  ...   \n",
              "\n",
              "           launch_to_deadline      launch_to_state_change  \\\n",
              "0  36 days 20:47:24.000000000  36 days 20:47:24.000000000   \n",
              "1  60 days 00:00:00.000000000  60 days 00:00:02.000000000   \n",
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              "4  32 days 06:02:33.000000000  32 days 06:02:33.000000000   \n",
              "\n",
              "  create_to_launch_days launch_to_deadline_days launch_to_state_change_days  \\\n",
              "0                    17                      36                          36   \n",
              "1                    10                      60                          60   \n",
              "2                     1                      60                          60   \n",
              "3                     0                      30                          30   \n",
              "4                     0                      32                          32   \n",
              "\n",
              "   SuccessfulBool  USorGB  TOPCOUNTRY  LaunchedTuesday DeadlineWeekend  \n",
              "0               0       1           1                0               0  \n",
              "1               0       1           1                0               0  \n",
              "2               0       1           1                0               0  \n",
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              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "\n",
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              "      background-color: #3B4455;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-a89277a1-457c-449b-a240-e8cd2527af9f button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-a89277a1-457c-449b-a240-e8cd2527af9f');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 60
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# display_df = full_1.iloc[:,:10]\n",
        "display_df = pd.concat([full_1.iloc[:,:10], full_1['state']], axis=1)\n",
        "display_df.head()\n",
        "# full_1.iloc[:,:10].corr()\n",
        "# heatmap = sns.heatmap(full_1.iloc[:,:10].corr(), vmin=-1, vmax=1, annot=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 406
        },
        "id": "lfDncHe5Py42",
        "outputId": "460e95ce-5e76-42a4-ac4f-6b76e6dd2efa"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
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              "    state                                               slug  \\\n",
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              "      <td>synopse-der-eu-dsgvo-artikel-erwagungsgrunde-bdsg</td>\n",
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              "\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-bdad7675-e2a4-4642-b8fa-160f8c877312');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "display_df['currency_symbol'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hJ4hdKTao_t_",
        "outputId": "bdb84d42-2a27-4e59-ceb7-c29e0ec3eb11"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "$      16139\n",
              "£       2498\n",
              "€       1618\n",
              "kr       283\n",
              "Fr        94\n",
              "Name: currency_symbol, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 64
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "display_df[display_df['currency_symbol']=='$']['currency'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "U2BAFTN7pF-G",
        "outputId": "f17e479e-88ec-4b38-fa1b-7be7e5493e0c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "USD    14141\n",
              "CAD     1098\n",
              "AUD      674\n",
              "NZD      111\n",
              "MXN       55\n",
              "HKD       35\n",
              "SGD       25\n",
              "Name: currency, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 67
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "nZWdZCN_pnqb"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}